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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive

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Speaker 1: from coast to coast with Caroline Hide in New York

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Speaker 1: and Eva Low in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up. Dell rises after almost

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Speaker 2: doubling its growth estimates for sales and profit through the

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Speaker 2: fiscal twenty thirty, boosted by demand for AI products.

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Speaker 3: As we speak with a key AI player, the CEO

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Speaker 3: of Core, We've joins us on the comedy's latest purchase

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Speaker 3: and a way in on the wave of compute deals.

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Speaker 2: And Tesla might unveil a new cheaper version of its

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Speaker 2: model why as soon as today.

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Speaker 4: We'll discuss what to expect.

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Speaker 3: Meanwhile, let's check in on these market said, which maybe

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Speaker 3: take a bit of a breather. Maybe there's some possibility

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Speaker 3: it's some profit taking. As we have just ramped higher

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Speaker 3: and higher day after day, notching new records in the

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Speaker 3: five hundred. We are flat on the Nasdaq one hundred.

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Speaker 3: Remember we still got a government has shut down on

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Speaker 3: our hands, but we do still see some buying of

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Speaker 3: some key names. What are you looking at?

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Speaker 2: Yeah, our top story is Dell, and much like the

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Speaker 2: broader market, it's lost a bit of steam. We were

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Speaker 2: up almost six percent earlier in the session, now up

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Speaker 2: two percent. Through the fiscal twenty thirty, they have almost

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Speaker 2: doubled their outlook. They're seeing top line growth seven nine percent,

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Speaker 2: bottom line growth of just an EPs fifteen percent. But

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Speaker 2: the story is really clear. Traction in the AI server business.

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Speaker 2: They have a backlog, margins will improve. It's worth digging

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Speaker 2: into it is.

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Speaker 3: And we do that. Obninburg's Brodie Ford, just how seismic

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Speaker 3: is this? To give us the guidance all the way

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Speaker 3: out to twenty thirty, you.

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Speaker 5: All said it great. It's AI servers, right. Somebody needs

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Speaker 5: to buy and video chips, package them into servers and

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Speaker 5: sell them to somebody else, and Dell has emerged as

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Speaker 5: a very successful company doing that. The opportunity appears larger

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Speaker 5: than Wall Street had anticipated. Sales are going to be

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Speaker 5: pretty healthy growth in the coming years. Though, of course,

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Speaker 5: as with a lot of AI infrastructure, the question is margins.

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Speaker 5: Those are going to remain pretty tight. Those operating margins

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Speaker 5: in the single digits, which often gives investors' anxiety. But

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Speaker 5: the growth rates are good enough that today doesn't matter.

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Speaker 2: The numbers are really interesting. So in the quarter gone.

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Speaker 2: Dell did booked five point six billion dollars worth of business,

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Speaker 2: They shipped more than eight billion dollars worth of servers,

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Speaker 2: and they have this like almost twelve billion dollar backlog.

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Speaker 2: And how they're explaining it is that server margins right

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Speaker 2: now are depressed because it costs money to move quickly.

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Speaker 2: I think that's the conclusion I'm getting anyway.

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Speaker 5: Yeah, that's right. I mean it costs a lot of

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Speaker 5: money to move quickly. These are massive deals. The supply

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Speaker 5: chain is tight, and so if you want to be

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Speaker 5: a buyer that gets priority, you're probably going to pay

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Speaker 5: a little more. The AI in for a market, whether

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Speaker 5: you're talking about compute servers really anybody, but in Vidia,

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Speaker 5: it's very competitive right now, and so if you want

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Speaker 5: to move with SKIN, you have to accept some lower margins.

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Speaker 5: Dell has been willing to do this, and it's winning

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Speaker 5: some big deals from companies like core Weave.

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Speaker 4: Cool Weave, big deal.

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Speaker 3: We talk about G forty two. We think about the

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Speaker 3: global impact here, But Brody, at the moment, we're in

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Speaker 3: this market where anything where you bolt on AI helps

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Speaker 3: your stock do relatively well.

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Speaker 4: Just talk to us about what.

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Speaker 3: IBM has been announcing and the folding into Panthropic.

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Speaker 5: IBM is another one of these companies seen as a

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Speaker 5: bit of a legacy company, forgotten a bit by the

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Speaker 5: average investor on Wall Street. But today they announce that

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Speaker 5: they're going to be using Anthropics Models for their coding assistant.

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Speaker 5: This matters because Anthropics model really is the favorite for

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Speaker 5: coding and so I think this is being taken as

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Speaker 5: a bit of a co sign for IBM's tool that hey,

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Speaker 5: large enterprises, you're not just going to pop into cursor.

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Speaker 5: You're probably going to do it through a more regulated environment,

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Speaker 5: and maybe IBM will be that vendor.

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Speaker 2: A slight tangent. But yesterday Brad Lightcap, whose open AI COO,

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Speaker 2: told me that Codex, which is their somewhat similar product,

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Speaker 2: the use of that is up ten x since August.

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Speaker 2: So and I noticed on social media there's a lot

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Speaker 2: of debate about like which one's better leave that to

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Speaker 2: the blomboy tech on us to decide. IBM does software.

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Speaker 2: I think a lot of people don't appreciate that this

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Speaker 2: story's indicative of that. Just explain what they offer exactly.

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Speaker 5: IBM offers a variety of software, whether it's in you know,

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Speaker 5: financial processing, transaction whether it's in coding assistant, it's a

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Speaker 5: lot of somewhat custom development helping large enterprises get all

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Speaker 5: of their data in order. Let's say run AI models

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Speaker 5: on it. Let's say, you know, use it your existing

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Speaker 5: data and your coding environment. They have a pretty wide swath,

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Speaker 5: and as you said, folks don't realize a lot that

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Speaker 5: it's their largest business segment at this point. This is

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Speaker 5: not the kind of outsourcing IBM of years past.

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Speaker 2: The most Brady Ford on some of what's happening in

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Speaker 2: tech today, Thank you very much. When Caroline and I

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Speaker 2: woke up this morning and sat at our desks, markets

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Speaker 2: were pushing higher. There was a lot of enthusiasm about AI,

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Speaker 2: and we've lost a lot of steam. I'm not saying

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Speaker 2: it's the fault of this program going to air, but

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Speaker 2: those major indices are now marginally in the red. There

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Speaker 2: are concerns that we are losing steam, and the words

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Speaker 2: AI and bubble keep coming up a lot. Let's get

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Speaker 2: a discussion with Janet Moui, RBC bring Dolphin, head of

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Speaker 2: market Analysis. All of these deals announced this week were

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Speaker 2: driving us at the index level when it comes to technology,

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Speaker 2: we're now losing steam. What is the principal direction of

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Speaker 2: travel here, Janet, when it comes to the tech sector, Hi.

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Speaker 6: Thanks for having me eds.

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Speaker 7: I do think that the Marcus having rallied very strongly

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Speaker 7: is almost like a strict line, particular for the chip companies.

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Speaker 6: So I think tiking a.

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Speaker 7: Breather is absolutely normal, and I think some investors would be.

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Speaker 6: So I'm not too worried about that.

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Speaker 7: I do think that the direction of travel would continue

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Speaker 7: to be atward because what we have seen is that

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Speaker 7: there are a lot of mega A ideals and they

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Speaker 7: involve a lot of infrastructure, a lot of CAPPAC spending

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Speaker 7: and its stays within the AI ecosystem, and I think

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Speaker 7: it just gives you a visibility over that longevity of

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Speaker 7: that AI spending.

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Speaker 4: Janet.

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Speaker 2: The driver in Monday's market was the deal between a

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Speaker 2: MD and open Ai. We spoke to a m D CEO, Lisa, Sue,

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Speaker 2: listen to this.

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Speaker 8: I have full confidence in open Ai, sm Greg Sarah.

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Speaker 8: I mean, this is a massive opportunity for us right now.

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Speaker 9: Right here.

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Speaker 8: It's about who has the most compute and how fast

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Speaker 8: can we get it online, and we're committing to doing

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Speaker 8: this together.

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Speaker 4: The question was.

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Speaker 2: Whether open ai was good for the money that it

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Speaker 2: needed to fund all of these projects, and the market

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Speaker 2: seems nervous about that.

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Speaker 4: How nervous about it are you?

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Speaker 6: So?

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Speaker 7: So far, I think the financing has been coming from

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Speaker 7: really investors and companies with very deep podcasts. I mean,

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Speaker 7: we're talking about the hyperscalers, including Nvidia's investment into opening Air.

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Speaker 6: That's one hundred billion there.

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Speaker 7: So I guess you know, from the liquidity perspective, that's

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Speaker 7: pretty ample, and so far we're not seeing a lot

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Speaker 7: of credit or debt financed activity going on into this

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Speaker 7: AI spending.

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Speaker 6: So I think on that front, time comfortable, and.

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Speaker 7: I think I think the key thing is that there's

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Speaker 7: just so much demand to compute out there, so many

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Speaker 7: companies can benefit from that and the building of the

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Speaker 7: infrastructure in AI. It involves not just a single company,

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Speaker 7: but really countries and many companies working together in the ecosystem.

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Speaker 6: So I believe that this this really gives you.

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Speaker 7: Visibility of the longevity of this AI trend going forward.

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Speaker 3: But the reporting keeps from coming back to us. Why

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Speaker 3: if there's unlimited and demand for compute, does AMD need

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Speaker 3: to give so called incentives it feels like to open

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Speaker 3: AI to share in on its own winnings the future revenue.

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Speaker 3: Why does the video have to put one hundred billion

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Speaker 3: dollars to work in terms of equity investment in open

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Speaker 3: AI if they should be just winning out for the

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Speaker 3: sheared demand and scale of compute. And why does Oracle

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Speaker 3: become one of the best performing stocks when clearly some

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Speaker 3: of the profit margins don't always accrue to an Oracle.

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Speaker 3: How do we decide which company really should win here?

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Speaker 7: Janet, Yes, so I think the big players in this

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Speaker 7: AI eqalsystem, in this build up of infrastructure, will likely

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Speaker 7: be clear beneficiaries.

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Speaker 6: I think that's more on the hardware, the equipment building

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Speaker 6: site of AI.

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Speaker 7: I mean, there will be definitely some big winners in

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Speaker 7: the software side of things, but we don't know what's

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Speaker 7: the next killer appso that's a bit more difficult. And

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Speaker 7: that's why I think the key favorite for investors remain

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Speaker 7: that AI infrastructure build out, whether you talk about data center,

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Speaker 7: cloud compute, and et cetera.

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Speaker 6: And I believe that, you know, I think some concern

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Speaker 6: is right.

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Speaker 7: A lot of this, you know, this close loop of

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Speaker 7: capital equality investment is based on confidence. It's really the

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Speaker 7: confidence that there's going to be insensuable demand for compute,

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Speaker 7: and it's really hard to gauge how much of that.

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Speaker 7: But if we do believe in this, the leaders in

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Speaker 7: the AI, I mean, Jason Juan talked a lot about

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Speaker 7: how the demand for compute is just going to be

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Speaker 7: so many, you know, tenfolds up from here. So I think,

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Speaker 7: you know, I would like to listen and believe in

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Speaker 7: the expert in terms of their vision on how much

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Speaker 7: there is on the computer demand and solar Far it

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Speaker 7: seems very very solid.

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Speaker 3: Yeah, promises and vision, But Janet, what data do you

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Speaker 3: turn to for hard fundamentals, because at the moment the

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Speaker 3: MIT report showed that some of these ultimate focuses on

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Speaker 3: productivity aren't actually paying off. Where is it that you're

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Speaker 3: going to get your confidence that can grounded in facts

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Speaker 3: not vision?

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Speaker 7: I mean, so far, if you look at the corporate

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Speaker 7: earnings growth, right, you look at the hyperscaler, they're still

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Speaker 7: delivering double digit earnings growth, and in fact, you can

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Speaker 7: attribute a lot of that to AI, the improved efficiency

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Speaker 7: in say advertising and cloud computing demand and things like that.

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Speaker 7: It's actually a lot of a big proportion of the

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Speaker 7: earnings delivery is already based on AI. And I think

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Speaker 7: there's still a lot of potential. And I think in

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Speaker 7: terms of the actual data, I think you just need

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Speaker 7: to look at the earnings revision. I mean typically you

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Speaker 7: can see today from Dell just one example, that earning

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Speaker 7: estimates and revenues keep being revised outwards, so there's really

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Speaker 7: clear visibility you're going to as far as twenty thirty.

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Speaker 7: So I think these are really hard data that you

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Speaker 7: can look at.

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Speaker 3: Januu, thank you for that read from RBC brew in Dolphin.

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Speaker 3: It's always so great to check.

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Speaker 2: In with you.

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Speaker 3: While coming up, we're going to speak with my trader

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Speaker 3: call We've CEO. It's going to be talking about the

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Speaker 3: latest AI deal that he's doing a bit of M

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Speaker 3: and A and where is he finding confidence for the

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Speaker 3: never ending wave of AI deals. This has pretty big

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Speaker 3: tech AI Hyperscala coll We've has announced it SA to

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Speaker 3: buy UK based Monolith AI, expanding beyond cloud infrastructure to

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Speaker 3: offer broader AI solutions, in this case to industrial and

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Speaker 3: manufacturing companies joining us. Now, Michael Intrader call We've CEO.

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Speaker 3: There's been a wave of M and A coming from me. Michael.

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Speaker 3: I want to understand why you're broadening out in this way.

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Speaker 10: Yeah, thank you very much for having me. It's exciting

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Speaker 10: to be back. And yes, we've been. We've been quite

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Speaker 10: active on the M and A front as we continue

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Speaker 10: to build and broaden our offerings. Many of them are

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Speaker 10: organic things that we're building internally and as you can

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Speaker 10: see with the model is a ideal. As you can

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Speaker 10: see you with the open pipe deal, as you can

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Speaker 10: see you with the weights and biases deal that we

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Speaker 10: did earlier this year. There is a tremendous focus that

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Speaker 10: we have on broadening out how we're going to be

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Speaker 10: able to support our clients from the software side. Obviously

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Speaker 10: there's also the core scientific transaction that is in process,

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Speaker 10: and once again it is part of our vision of

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Speaker 10: being able to offer a turnkey solution from the bricks

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Speaker 10: all the way up through the infrastructure and through the

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Speaker 10: software to be able to serve our customers in the

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Speaker 10: best way possible.

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Speaker 3: And is that because also it's more profitable, Michael, We're

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Speaker 3: looking at reports at the moment about Oracle and ultimately

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Speaker 3: how Razu thin its profit margins are when you're thinking

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Speaker 3: about renting out compute because of the cost of ultimately

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Speaker 3: the GPUs coming from Nvidia, how hard is it to

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Speaker 3: make your bread and butter work? From a real profit

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Speaker 3: margin perspective, Yeah.

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Speaker 10: Look, you know, the profit margins we're able to garner

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Speaker 10: with the infrastructure that we sell are significant.

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Speaker 9: We're excited about it.

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Speaker 10: We've really been able to drive our business in accordance

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Speaker 10: with our objectives. We're scaling at an incredibly fast paced

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Speaker 10: and so with that you get short term distortions, but

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Speaker 10: in terms of the business strategy and execution, couldn't be

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Speaker 10: happier when you think about where the space is today

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Speaker 10: and where the space is going to be over the

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Speaker 10: next several years. The broadening out of our offering of

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Speaker 10: software solutions really allows for an incredibly effective way of

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Speaker 10: bringing on new clients that are going to pay for

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Speaker 10: not only the infrastructure but also the services that they

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Speaker 10: get when they need to be able to integrate artificial

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Speaker 10: intelligence into their broader mission. And so we're excited about that.

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Speaker 10: We think it's the right way to go. We've been

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Speaker 10: aggressively pursuing it. We brought on some great teams and

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Speaker 10: you know you'll be seeing products coming out of those

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Speaker 10: teams imminently.

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Speaker 2: Michael, The top story today is Dell roughly doubling its

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Speaker 2: growth projections for both sales and profit through fiscal twenty

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Speaker 2: thirty largely because of AI server demand. And you are

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Speaker 2: one of the key customers for Dell in that respect.

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Speaker 2: From the customer's perspective, what does that kind of bigger

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Speaker 2: picture forecast from Dell signal to you.

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Speaker 10: Look, you know, there's a lot of noise in the

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Speaker 10: space again, and this happens periodically, and you know, but

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Speaker 10: when you take a step back, you're seeing incredibly strong

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Speaker 10: demand from Dell. You're seeing incredibly strong demand across the

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Speaker 10: hyperscalers as they're able to embed AI into their products.

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Speaker 10: You know, the profits that those are driving are the underpinnings.

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Speaker 9: You're asking about what people look to.

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Speaker 10: That's what they look to, right like, they look to

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Speaker 10: people that are able to generate revenue from their existing

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Speaker 10: client base using AI.

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Speaker 9: And that is.

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Speaker 10: Incredibly strong and we've seen it repeatedly. You're seeing it

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Speaker 10: again with Dell. It's really exciting. And once again you

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Speaker 10: zoom out just a bit here and it's really uh

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Speaker 10: an incredible space going through an incredible transition. That transition

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Speaker 10: is causing a systemic imbalance in.

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Speaker 9: The infrastructure side, which is what drove us towards UH,

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Speaker 9: the UH.

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Speaker 10: The deal UH that we are looking at with Course Scientific.

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Speaker 10: Course Scientific is an infrastructure provider for us UH. They

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Speaker 10: are one of many, you know, over the since our

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Speaker 10: last earnings call, we've increased our UH contracted pipeline of

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Speaker 10: power from two point two gigawatts to now up to

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Speaker 10: two point eight gigawatts, which is a new number that

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Speaker 10: we're putting out there, of which none of that comes

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Speaker 10: from Course Scientific. We have broadened our strategic relationships with

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Speaker 10: other priortividers of the infrastructure. A great example of that

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Speaker 10: is Galaxy Digital, you.

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Speaker 9: Know, where where we're able to go ahead and and and.

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Speaker 10: Get large blocks of contiguous power to continue to buy

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Speaker 10: infrastructure that will be made available to our clients as

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Speaker 10: they continue to build. And ultimately that brings us back

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Speaker 10: to this particular acquisition that we're looking at.

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Speaker 9: You know, it's an acquisition that we put out there

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Speaker 9: several months ago.

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Speaker 10: Of course, Scientific provides core Weave with over five hundred

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Speaker 10: megawatts worth of infrastructure which we currently have contracted. Therefore,

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Speaker 10: you know, we have a great relationship with them. Regardless

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Speaker 10: of the outcome of this UH acquisition, we will continue

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Speaker 10: to have a great relationship with them as they deliver

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Speaker 10: power to us.

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Speaker 9: Within our data centers that we share with them.

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Speaker 10: It is a small and shrinking part of our portfolio,

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Speaker 10: and ultimately that led us to, uh, you know, the

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Speaker 10: position where you know, really, under no circumstances will we

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Speaker 10: readdress the bid that we put out. That's the number.

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Speaker 10: We think it fitly represents the value for them. We

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Speaker 10: think it will be great for the two companies to

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Speaker 10: move forward together. The systemic imbalance within the infrastructure is

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Speaker 10: causing you know, it really is stressing the supply chains

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Speaker 10: and cause all kinds of delays.

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Speaker 2: Yeah, I'm sorry to cut you off. We're going to

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Speaker 2: run short of time, and I've got to ask you this.

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Speaker 2: Twenty four hours ago, we had AMD's CEO Lisa Sue

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Speaker 2: and open AI president Greg Brockman on the program. There

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Speaker 2: are lots of unasked questions about the six gigawats of

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Speaker 2: capacity they've agreed will call. We participate and support in

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Speaker 2: that arrangement.

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Speaker 4: Just very briefly.

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Speaker 10: Yeah, So we support OPENINGI enormously across the space, and

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Speaker 10: we have great relationships with AMD. We use their infrastructure

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Speaker 10: within our portfolio. How they choose to divvy that out.

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Speaker 9: We don't know yet.

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Speaker 10: You know, we're more focused on the fourteen you know,

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Speaker 10: the minimum deal that we did two weeks ago, which

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Speaker 10: was a minimum of fourteen point two billion dollars, which

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Speaker 10: will continue to spand with Meta that will come online

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Speaker 10: in twenty twenty six. We're really excited about that. And

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Speaker 10: you know, the the AMD deal with Opening Eye is

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Speaker 10: just another example of the recognition across the space of

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Speaker 10: how much of this infrastructure is required and how much

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Speaker 10: demand all of these providers of artificial intelligence are encountering.

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Speaker 2: Michael and Trader of Koby, thank you very much for

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Speaker 2: being back on Bloomberg Tech. Now coming out, Tessa's set

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Speaker 2: to unveil a more affordable version of its model.

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Speaker 4: Why we have more on that next.

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Speaker 2: This is Bloomberg.

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Speaker 11: Tech's time now for Talking Tech and first Up Bank

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Speaker 11: of New York Mellon But is exploring tokenized deposits, enabling

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Speaker 11: clients to make payments using rock chain technology.

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Speaker 3: We look at speed up settlement time, reduced costs. Other banks,

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Speaker 3: including JP, Morgan and HSBC I've made similar product moves.

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Speaker 3: Plus app Lemon, while it's facing a probe over its

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Speaker 3: data collection practices. According to sources, the Securities and Exchange

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Speaker 3: Commission is investigating whether Apple and violated service agreements on

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Speaker 3: pushing targeted ads. Have Love and declined to comment on

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Speaker 3: the matter. And Elil Musk named a former Morgan Stanley

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Speaker 3: executive as the chief financial officer of XAI. It's all

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Speaker 3: according to reporting The Financial Times, Anthony Armstrong worked on

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Speaker 3: Musk's purchase of Twitter. He will oversee the finances and

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Speaker 3: Musk's AI startup and the social media platform now called

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Speaker 3: x Of course ed.

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Speaker 2: Tesla is set to unveil a new cheaper version of

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Speaker 2: its model Y as soon as today. That's according to sources.

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Speaker 2: Bloomberg's Craige Trudell Our Global Autos are joins us from London.

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Speaker 2: You and I worked on this together. This is what

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Speaker 2: I'm hearing from sources inside Tesla that it is just

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Speaker 2: a more affordable model. Why fewer features They engineered cost

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Speaker 2: out of the battery pack and the motor. But also

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Speaker 2: it's kind of been hiding in plain sight because must

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Speaker 2: and others discuss this on the most recent earnings. Cool.

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Speaker 12: Yeah, one of the more colorful moments on that call was,

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Speaker 12: you know, some of the other executives at the company

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Speaker 12: kind of dancing around these questions about what this more

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Speaker 12: affordable Tesla would be and must just coming right out

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Speaker 12: and saying, let's let the cat out of the bag.

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Speaker 12: It's it's just a model. Why so, you know, I

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Speaker 12: think the expectation here, of course, is that this by

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Speaker 12: by taking some of the content out of the vehicle,

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Speaker 12: maybe you know, making it a little bit less attractive

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Speaker 12: from from a range perspective, but more attractive from a

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Speaker 12: price perspective.

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Speaker 7: You know.

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Speaker 12: The hope here is that that some incremental consumers who

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Speaker 12: maybe we're going to be priced out of this vehicle now,

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Speaker 12: can can maybe afford it with this seventy five hundred

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Speaker 12: dollars tax credit going away. And I think that's going

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Speaker 12: to be you know, one of the key questions for

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Speaker 12: the next earnings call from Tesla is you know, just

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Speaker 12: how how steep of a cliff are we looking at here?

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Speaker 4: Now that that.

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Speaker 12: Incentive has been sort of pulled out from under the industry.

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Speaker 3: I can see that that reacts to the finding of

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Speaker 3: the tax credit, But there's been this ongoing call for

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Speaker 3: them to offer a less costly version of the ev

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Speaker 3: largely because of China competition. Is it enough?

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Speaker 12: I think, you know, that's a really fair question. And

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Speaker 12: Ed's reported on this going back quite a while that

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Speaker 12: you know, Elon Musk is not particularly interested in expanding

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Speaker 12: the lineup with an altogether new vehicle when his in

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Speaker 12: his mind, this is a company that's on the cusp

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Speaker 12: of making vehicles capable of driving themselves. And so you

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Speaker 12: know why sort of you know, bother with with introducing

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Speaker 12: a more affordable vehicle and competing with the likes of

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Speaker 12: a Corolla or a Civic when you know what you

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Speaker 12: have in the lineup is on the cusp of doing

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Speaker 12: something that you know no other manufacturer is going to

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Speaker 12: be capable of doing. The question, of course, is can

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Speaker 12: he make good on that sort of you know, promise

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Speaker 12: or vision.

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Speaker 2: You know, Craig and Caroline Tesla did not respond to

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Speaker 2: our requests for comment, and you know, there's a lot

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Speaker 2: of speculation out there that it could be a roads

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Speaker 2: and we're not expecting some big event. You know, Craig,

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Speaker 2: you've been editing this stuff with me. The frank reality

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Speaker 2: is we just don't know. But Caro, you know, we're

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Speaker 2: waiting to see what happens.

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Speaker 3: We do, we'll wait for it to drop, even if

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Speaker 3: it's stealth mode, but you're never in stealth with your reporting,

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Speaker 3: and Craig, we thank you for this is the editor

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Speaker 3: on it. We appreciate your time. I meanwhile coming up

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Speaker 3: look open Aiyes, Golden Touch, how companies are benefiting. I'm

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Speaker 3: just going to mention of the AI Darling, that's next.

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Speaker 3: This is Blumbad Tech.

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Speaker 4: Welcome back to Bloomberg Tech.

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Speaker 2: Yesterday afternoon, I'm sat in a warehouse in Fort Mason,

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Speaker 2: San Francisco. Sam Ottman of Open Eyes on stage. Loads

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Speaker 2: of open Ai execs are on stage. They name check

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Speaker 2: all of these companies and some of the stocks go ballistic.

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Speaker 2: One of them is Figma, and Figma basically spikes up

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Speaker 2: sixteen percent at one point, and yesterday said closes up

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Speaker 2: seventy percent. It's up again for a second day, all

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Speaker 2: because of a name check on stage by open Ai.

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Speaker 2: Actually one quick stack carrot. Figma's up for the first

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Speaker 2: time for four straight days since it listed in July,

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Speaker 2: so it's on a bit of a run anyway. But yeah,

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Speaker 2: let's dig into what's happening with the Golden Touch.

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Speaker 3: Let's because the guy's been writing all about our equities reporter, right,

441
00:23:23,080 --> 00:23:25,880
Speaker 3: nos selca been looking at this so called golden touch

442
00:23:25,960 --> 00:23:28,960
Speaker 3: for many a name that sawed yesterday, Figma really holding

443
00:23:29,000 --> 00:23:31,520
Speaker 3: onto those games. Look, they get name checked, but you

444
00:23:31,560 --> 00:23:34,440
Speaker 3: are seeing a folding in of the software within chat ept.

445
00:23:34,800 --> 00:23:36,520
Speaker 3: It's almost a bit of a lifeline when we're worried

446
00:23:36,520 --> 00:23:38,040
Speaker 3: that some of these companies were going to be made

447
00:23:38,119 --> 00:23:39,880
Speaker 3: redundant in some way by open Ai.

448
00:23:41,280 --> 00:23:43,960
Speaker 13: Yes, absolutely, there's been a lot of concern that open

449
00:23:44,000 --> 00:23:46,600
Speaker 13: Ai or these other large language models would really start

450
00:23:46,680 --> 00:23:50,080
Speaker 13: to eat the lunch of these more established legacy software companies.

451
00:23:50,280 --> 00:23:54,360
Speaker 13: We saw all kinds of mentioned yesterday other companies including HubSpot,

452
00:23:54,680 --> 00:23:57,240
Speaker 13: Salesforce is really going on down the line, and I

453
00:23:57,240 --> 00:23:59,879
Speaker 13: think there's a little bit of relief that open aim

454
00:24:00,200 --> 00:24:03,480
Speaker 13: be working with these companies integrating them into its service,

455
00:24:03,720 --> 00:24:06,360
Speaker 13: as opposed to just you know, offering sort of competing

456
00:24:06,440 --> 00:24:10,240
Speaker 13: services that might really represent a strong force of competition

457
00:24:10,359 --> 00:24:12,960
Speaker 13: for them. So yeah, these kinds of mentions we really

458
00:24:13,000 --> 00:24:17,720
Speaker 13: saw some immediate spikes yesterday really across sectors across the market.

459
00:24:17,960 --> 00:24:20,960
Speaker 13: Online travel companies, even Mattel saw a little bit of

460
00:24:20,960 --> 00:24:23,760
Speaker 13: a pop after it was mentioned. And it's a demonstration

461
00:24:23,800 --> 00:24:25,720
Speaker 13: of Sora the video generation service.

462
00:24:27,000 --> 00:24:30,320
Speaker 2: And you reflecting your piece about how if open aiyes

463
00:24:30,440 --> 00:24:32,600
Speaker 2: has the golden touch in AI, it's really been in

464
00:24:32,680 --> 00:24:35,200
Speaker 2: Nvidia that's been the golden ticket and had a similar

465
00:24:35,240 --> 00:24:36,480
Speaker 2: effect on other stocks.

466
00:24:37,560 --> 00:24:37,720
Speaker 14: Yeah.

467
00:24:37,720 --> 00:24:39,600
Speaker 13: Absolutely, So this is something that we've been seeing for

468
00:24:39,800 --> 00:24:41,919
Speaker 13: as long as AI has been a major company or

469
00:24:42,200 --> 00:24:44,600
Speaker 13: major theme in markets. And of course in addition to

470
00:24:45,040 --> 00:24:47,359
Speaker 13: all the companies we've been talking about. Obviously yesterday we

471
00:24:47,440 --> 00:24:50,159
Speaker 13: had the huge jump in AMD on the back of

472
00:24:50,200 --> 00:24:52,600
Speaker 13: the news with open Ai. We had last month huge

473
00:24:52,600 --> 00:24:54,959
Speaker 13: gains in Oracle. So certainly this has been to trend

474
00:24:55,320 --> 00:24:57,320
Speaker 13: all these companies that are really seen at the cutting

475
00:24:57,440 --> 00:25:00,160
Speaker 13: edge of AI, anything that sort of like has any

476
00:25:00,240 --> 00:25:02,680
Speaker 13: kind of connection to them. We do see stock reactions now.

477
00:25:02,880 --> 00:25:05,119
Speaker 13: In many cases the stocks pulled back today. I mean

478
00:25:05,160 --> 00:25:07,840
Speaker 13: you mentioned Figma maybe up still, but I know Salesforce

479
00:25:07,920 --> 00:25:09,600
Speaker 13: was down, some of these other stocks down today. So

480
00:25:09,600 --> 00:25:12,400
Speaker 13: it's not proving to be a lasting bounce, but certainly

481
00:25:12,720 --> 00:25:14,440
Speaker 13: just a mere excitement. It seems like it's getting a

482
00:25:14,440 --> 00:25:16,119
Speaker 13: lot of people, at least in the short term excited.

483
00:25:16,880 --> 00:25:19,000
Speaker 2: Blue most rhyme for Stellaka on the moves that matter,

484
00:25:19,119 --> 00:25:21,320
Speaker 2: Thank you very much. So we've talked about Figma, we've

485
00:25:21,359 --> 00:25:23,760
Speaker 2: just shown it just then one of the names that

486
00:25:23,840 --> 00:25:27,200
Speaker 2: absolutely spiked after the mention on stage from Sam Altman

487
00:25:27,280 --> 00:25:30,159
Speaker 2: and open Ai it's going to be integrated into chat

488
00:25:30,320 --> 00:25:33,159
Speaker 2: GPT through an API, a third party. It was one

489
00:25:33,160 --> 00:25:35,480
Speaker 2: of the key pieces of news from Opienais dev day.

490
00:25:35,680 --> 00:25:38,800
Speaker 2: We've got to sit down with Pigma CEO Dylan Field.

491
00:25:40,240 --> 00:25:43,639
Speaker 15: There wasn't really like a negotiation of any kind. It

492
00:25:43,680 --> 00:25:48,320
Speaker 15: was a collaboration. And are you know me our engineers,

493
00:25:48,320 --> 00:25:50,840
Speaker 15: our frog people. We're talking with their engineers, their Frog people.

494
00:25:51,359 --> 00:25:53,800
Speaker 15: We just have like a slack channel going. I was

495
00:25:53,840 --> 00:25:56,760
Speaker 15: literally do I mean their engineers up to think midnight

496
00:25:56,840 --> 00:26:00,000
Speaker 15: last night? Wow, just identifying longtail issues that they're checking

497
00:26:00,080 --> 00:26:02,720
Speaker 15: out to make sure everything's ready for your day. And

498
00:26:02,920 --> 00:26:05,960
Speaker 15: the team has been amazing to work with, and yeah,

499
00:26:06,119 --> 00:26:09,240
Speaker 15: just in general, been very thankful for the partnership and

500
00:26:09,480 --> 00:26:10,840
Speaker 15: the chance to go build us to figure that.

501
00:26:10,840 --> 00:26:12,679
Speaker 4: Out on the chatterbuty system.

502
00:26:13,080 --> 00:26:15,679
Speaker 2: Dylan, I know that you probably weren't paying attention to

503
00:26:15,720 --> 00:26:19,359
Speaker 2: this particular point, but during the early part of the keynote,

504
00:26:19,680 --> 00:26:23,800
Speaker 2: Figmas shares when ballistic. Frankly, many other names did as well.

505
00:26:23,840 --> 00:26:26,600
Speaker 2: When they were going through the list of partners that

506
00:26:26,800 --> 00:26:30,040
Speaker 2: will be at API access through the chat GPT.

507
00:26:30,800 --> 00:26:32,320
Speaker 4: What does that signal to you.

508
00:26:32,359 --> 00:26:35,880
Speaker 2: About you know, when open ai communicates there is that

509
00:26:36,040 --> 00:26:39,919
Speaker 2: level of response to your from your investors and the

510
00:26:40,000 --> 00:26:41,560
Speaker 2: technology industry at large.

511
00:26:42,040 --> 00:26:44,840
Speaker 15: Yeah, you surprised me with that earlier before we started

512
00:26:44,840 --> 00:26:48,760
Speaker 15: talking about an interview, and I'll a schecond later. But

513
00:26:49,560 --> 00:26:52,639
Speaker 15: I don't know as the honest answer, because there's not

514
00:26:52,680 --> 00:26:56,040
Speaker 15: really something that I'm as tuned into. I told the

515
00:26:56,080 --> 00:26:59,800
Speaker 15: team before we iPod, during the IPO. After the IPO

516
00:27:00,359 --> 00:27:03,800
Speaker 15: number goes up, number goes down. What matters of the

517
00:27:03,880 --> 00:27:06,280
Speaker 15: inputs every day We've got to be driving to make

518
00:27:06,280 --> 00:27:08,840
Speaker 15: sure that we are making a better user experience, better

519
00:27:08,920 --> 00:27:12,280
Speaker 15: products for all of our users on the platform. And

520
00:27:12,359 --> 00:27:16,080
Speaker 15: so I think if it means anything to me, people

521
00:27:16,080 --> 00:27:18,200
Speaker 15: see possibility.

522
00:27:17,960 --> 00:27:19,399
Speaker 4: And how these systems can work together.

523
00:27:20,000 --> 00:27:21,760
Speaker 15: But now we have to go make sure that we

524
00:27:21,840 --> 00:27:24,919
Speaker 15: prove it and then it's great and hopefully it's just

525
00:27:24,920 --> 00:27:25,280
Speaker 15: a start.

526
00:27:25,359 --> 00:27:28,080
Speaker 4: There's a lot more we can do very quickly before

527
00:27:28,119 --> 00:27:28,720
Speaker 4: we let you go.

528
00:27:28,960 --> 00:27:31,800
Speaker 2: You know, you talk, it's about speaking with the slacking

529
00:27:31,880 --> 00:27:35,000
Speaker 2: the open ai engineering team until very late last night,

530
00:27:35,640 --> 00:27:37,600
Speaker 2: just as a moment in time like this dev day

531
00:27:37,640 --> 00:27:39,720
Speaker 2: where there are thousands of people here in Fort Mason,

532
00:27:39,760 --> 00:27:44,520
Speaker 2: San Francisco, in your technology career, could you try and

533
00:27:44,560 --> 00:27:47,560
Speaker 2: summarize what you think is happening in particular with AI

534
00:27:47,640 --> 00:27:49,320
Speaker 2: and what's happening in this city.

535
00:27:49,480 --> 00:27:51,120
Speaker 4: I think it's a moment of excitement.

536
00:27:52,119 --> 00:27:55,520
Speaker 15: And I mean, look, if you're an engineer, if you're

537
00:27:55,520 --> 00:27:58,400
Speaker 15: a designer or a product person, what do you love?

538
00:27:58,440 --> 00:28:02,040
Speaker 15: You love new toys and there are new toys every

539
00:28:02,160 --> 00:28:04,920
Speaker 15: week or two right now. Toys you can go build

540
00:28:04,960 --> 00:28:08,280
Speaker 15: with things that you can go and use to invent

541
00:28:08,320 --> 00:28:12,919
Speaker 15: the future and create new workflows. That's exciting for a technologist.

542
00:28:13,520 --> 00:28:16,560
Speaker 15: And you know where all it goes. Nobody knows if

543
00:28:16,600 --> 00:28:19,720
Speaker 15: they tell you, they do their lines you or to themselves.

544
00:28:20,520 --> 00:28:23,520
Speaker 15: I don't know where everything's headed. But I think that

545
00:28:23,840 --> 00:28:27,360
Speaker 15: definitely it's a moment of excitement right now, and we're

546
00:28:27,440 --> 00:28:29,239
Speaker 15: excited about all the change we can make for our

547
00:28:29,320 --> 00:28:32,120
Speaker 15: users and how we can make their experience using Figma matter.

548
00:28:33,359 --> 00:28:37,400
Speaker 3: Such a great conversation ed there with Pigma CEO Denn Field. Meanwhile,

549
00:28:37,840 --> 00:28:41,239
Speaker 3: NYSEC owner Intercontinental Exchange it puts to invest as much

550
00:28:41,240 --> 00:28:44,720
Speaker 3: as two billion dollars in cash into Polymarket, following the

551
00:28:44,720 --> 00:28:47,560
Speaker 3: crypto based betting platform at roughly eight billion dollars from

552
00:28:47,560 --> 00:28:50,120
Speaker 3: all being most cafin dooldy here with the news, and

553
00:28:50,200 --> 00:28:53,680
Speaker 3: it's interesting they're betting on the future growth of this company,

554
00:28:53,720 --> 00:28:57,400
Speaker 3: but also using its data within nys is offering.

555
00:28:57,480 --> 00:28:57,920
Speaker 4: That's right.

556
00:28:58,000 --> 00:29:02,120
Speaker 16: The data is really the value that polymarket can provide

557
00:29:02,160 --> 00:29:05,480
Speaker 16: to ICE and its client base. So these are large

558
00:29:05,520 --> 00:29:09,200
Speaker 16: institutions used to trading on the New York Stock Exchange

559
00:29:09,480 --> 00:29:14,440
Speaker 16: options exchanges that ICE operates, and now those users are

560
00:29:14,480 --> 00:29:19,200
Speaker 16: going to be having the ability to pull from Polymarket's data.

561
00:29:19,360 --> 00:29:23,720
Speaker 16: Data is an incredibly valuable part of exchange operators how

562
00:29:23,800 --> 00:29:26,720
Speaker 16: they're growing their own business. And at the same time

563
00:29:27,280 --> 00:29:31,480
Speaker 16: this announcement this morning, there was another part about tokenization.

564
00:29:31,640 --> 00:29:35,880
Speaker 16: That's another path forward for these exchanges as they're looking

565
00:29:35,960 --> 00:29:39,640
Speaker 16: to innovate, and if you're a storied institution like ICE,

566
00:29:39,960 --> 00:29:43,200
Speaker 16: you might not be able to do that without these

567
00:29:43,640 --> 00:29:47,280
Speaker 16: new incumbents, the crypt native firms that have already started

568
00:29:47,560 --> 00:29:51,640
Speaker 16: to build and to tokenize themselves. Now they can come

569
00:29:51,640 --> 00:29:54,160
Speaker 16: forward with their own ideas and partner with ICE in

570
00:29:54,200 --> 00:29:54,600
Speaker 16: this way.

571
00:29:55,760 --> 00:29:58,280
Speaker 2: Betting on prediction markets was a story around the twenty

572
00:29:58,280 --> 00:30:01,360
Speaker 2: twenty four US presidential election, and so I don't know like,

573
00:30:01,520 --> 00:30:04,560
Speaker 2: give us your reporting on the deal itself to invest

574
00:30:04,720 --> 00:30:07,560
Speaker 2: This is something that moved very quickly. It's something that

575
00:30:07,800 --> 00:30:09,560
Speaker 2: you know, they've been talking about for a while.

576
00:30:10,080 --> 00:30:14,760
Speaker 16: So the prediction market is a competitive space. It's been growing.

577
00:30:15,400 --> 00:30:18,280
Speaker 16: You have the likes of Calshi and Crypto dot Com.

578
00:30:18,600 --> 00:30:21,640
Speaker 16: These are all companies that have started to put forth

579
00:30:21,920 --> 00:30:24,640
Speaker 16: predictions in the form of In many cases it's a

580
00:30:24,640 --> 00:30:28,600
Speaker 16: binary yes or no, and you can apply this to markets,

581
00:30:28,640 --> 00:30:32,080
Speaker 16: and I believe that is where this deal itself is

582
00:30:32,120 --> 00:30:35,120
Speaker 16: going to start. It's going to be a simple will

583
00:30:35,200 --> 00:30:38,240
Speaker 16: the value of bold, for example, or another asset class

584
00:30:38,920 --> 00:30:41,240
Speaker 16: cross a certain benchmark and it's going to be a

585
00:30:41,320 --> 00:30:44,040
Speaker 16: yes or no and go from there. But you can

586
00:30:44,120 --> 00:30:49,280
Speaker 16: also extend that to as you mentioned politics. Eventually sports

587
00:30:49,320 --> 00:30:53,760
Speaker 16: will be another very big potential asset class that can

588
00:30:53,840 --> 00:30:57,600
Speaker 16: expand there's questions around regulation of how that might work.

589
00:30:57,840 --> 00:31:02,440
Speaker 16: But if you have companies like earlier we saw CME,

590
00:31:02,560 --> 00:31:06,560
Speaker 16: the largest derivatives exchange based in Chicago. They're partnering with

591
00:31:06,680 --> 00:31:10,280
Speaker 16: fan Duel. Everyone is racing to partner up, so I

592
00:31:10,360 --> 00:31:12,920
Speaker 16: expect to see many more deals like this that will

593
00:31:12,920 --> 00:31:17,640
Speaker 16: indicate where the future of exchange operators are going what a.

594
00:31:17,600 --> 00:31:21,200
Speaker 3: Difference year or so, Mikes, because you mentioned regulation and

595
00:31:21,280 --> 00:31:24,000
Speaker 3: there is a much more favorable regulatory environment. I mean, look,

596
00:31:24,040 --> 00:31:26,680
Speaker 3: Poni Marcus coming back to the US and previously not

597
00:31:26,680 --> 00:31:27,880
Speaker 3: been allowed to be here. That's right.

598
00:31:27,920 --> 00:31:31,280
Speaker 16: In twenty twenty two, this was a company that was

599
00:31:31,720 --> 00:31:35,120
Speaker 16: shunned away from the US marketplace. They kept many of

600
00:31:35,160 --> 00:31:39,040
Speaker 16: their users, but they couldn't embrace us in the way

601
00:31:39,080 --> 00:31:42,360
Speaker 16: that they wanted to. And now flash forward to today,

602
00:31:42,600 --> 00:31:46,600
Speaker 16: They've bought a derivatives operator that was very It was

603
00:31:46,640 --> 00:31:49,720
Speaker 16: not well known, but it basically was a path forward

604
00:31:49,720 --> 00:31:52,640
Speaker 16: to them to re enter the US marketplace. They have

605
00:31:52,720 --> 00:31:56,560
Speaker 16: regulators that they're working with. Just a few days ago,

606
00:31:56,880 --> 00:32:01,360
Speaker 16: we had companies like Ice and Polymarket, the executives going

607
00:32:01,400 --> 00:32:04,760
Speaker 16: to DC and speaking with the SEC and the CFTC.

608
00:32:04,880 --> 00:32:10,000
Speaker 16: These are the regulators of the main, the largest marketplaces

609
00:32:10,000 --> 00:32:13,880
Speaker 16: when you think about equities options, and now we're going

610
00:32:13,880 --> 00:32:18,040
Speaker 16: to see prediction markets potentially come under those same regulators.

611
00:32:18,320 --> 00:32:21,240
Speaker 16: So we see a lot of partnering up. We see

612
00:32:21,280 --> 00:32:25,640
Speaker 16: a path forward of innovation and really an embrace of

613
00:32:25,960 --> 00:32:29,320
Speaker 16: the crypto native firms like a Polymarket.

614
00:32:29,680 --> 00:32:33,040
Speaker 2: Bloomer's Cafine Dougherty, thank you very much. Okay, more to

615
00:32:33,080 --> 00:32:35,720
Speaker 2: come next on open ai. We'll be right back. This

616
00:32:35,800 --> 00:32:51,640
Speaker 2: is Bloomberg Tech. Open ai is announced blockbuster deals with

617
00:32:51,680 --> 00:32:55,040
Speaker 2: AMD and Nnvidia to build out data centers that combined

618
00:32:55,080 --> 00:32:58,080
Speaker 2: would have more than enough electricity to power New York

619
00:32:58,160 --> 00:33:01,080
Speaker 2: City a peak demand open Air as chief operating off

620
00:33:01,080 --> 00:33:03,880
Speaker 2: to brad Lightcap explain why the company is going so

621
00:33:04,040 --> 00:33:05,440
Speaker 2: big on infrastructure.

622
00:33:05,600 --> 00:33:09,080
Speaker 14: We are tremendously compute constrained. It feels like we're in

623
00:33:09,120 --> 00:33:11,400
Speaker 14: this kind of recurring theme of being compute constrained. And

624
00:33:11,680 --> 00:33:13,480
Speaker 14: I think the reason for that is the answer to

625
00:33:13,520 --> 00:33:15,040
Speaker 14: the question you ask, which is demand.

626
00:33:15,320 --> 00:33:16,240
Speaker 4: Right, we see.

627
00:33:16,040 --> 00:33:19,000
Speaker 14: There are multiples of demand that are lateent and untapped

628
00:33:19,840 --> 00:33:22,800
Speaker 14: from what we have today. And even today, obviously by

629
00:33:22,840 --> 00:33:26,520
Speaker 14: any standard, demand in revenue growth has been torrid in

630
00:33:27,040 --> 00:33:29,880
Speaker 14: its pace, and so really we have to invest ahead

631
00:33:29,880 --> 00:33:31,160
Speaker 14: of that. And I think that's going to be the

632
00:33:31,200 --> 00:33:33,080
Speaker 14: rate limitter for us to be able to go capture

633
00:33:33,240 --> 00:33:35,959
Speaker 14: a demand, whether it's consumer or enterprise, and for us

634
00:33:35,960 --> 00:33:38,920
Speaker 14: to be able to build new models, paralyze more experiences,

635
00:33:39,000 --> 00:33:42,200
Speaker 14: more product experiences, and then enable users specifically to be

636
00:33:42,200 --> 00:33:45,080
Speaker 14: able to use those products more actively.

637
00:33:45,240 --> 00:33:46,080
Speaker 4: In their daily life.

638
00:33:46,080 --> 00:33:48,680
Speaker 14: At work and at home, and so you know, even

639
00:33:48,720 --> 00:33:51,240
Speaker 14: things like Sora, the app we just launched. We wish

640
00:33:51,280 --> 00:33:54,120
Speaker 14: we could invite more people onto it now, but we

641
00:33:54,160 --> 00:33:56,719
Speaker 14: just need more compute. So the AMD deal we're excited

642
00:33:56,760 --> 00:34:00,520
Speaker 14: about being you know, directionally a way.

643
00:34:00,400 --> 00:34:03,040
Speaker 4: For us to do that. I've got to ask about

644
00:34:03,040 --> 00:34:03,960
Speaker 4: the report that.

645
00:34:03,960 --> 00:34:07,720
Speaker 2: Open AI closed secondary or the ability for employees to

646
00:34:07,720 --> 00:34:10,799
Speaker 2: sell shares at a five hundred billion dollar valuation. I

647
00:34:10,840 --> 00:34:13,080
Speaker 2: already asked you this question, but what is the metric

648
00:34:13,320 --> 00:34:16,040
Speaker 2: we're supposed to judge your success by the five hundred

649
00:34:16,080 --> 00:34:20,520
Speaker 2: billion dollar valuation? The six billion tokens per minute? To you, Brad,

650
00:34:20,520 --> 00:34:20,960
Speaker 2: what is it?

651
00:34:21,680 --> 00:34:21,920
Speaker 15: For me?

652
00:34:21,960 --> 00:34:26,840
Speaker 14: It's it's actually kind of a metric that we talked about.

653
00:34:26,840 --> 00:34:27,720
Speaker 4: Is tokens.

654
00:34:27,840 --> 00:34:32,440
Speaker 14: It's you mentioned six billion tokens per minute on our API.

655
00:34:33,120 --> 00:34:35,720
Speaker 4: That is the purest for me, the kind of essence

656
00:34:35,800 --> 00:34:38,040
Speaker 4: of utility is that consumption metric.

657
00:34:38,120 --> 00:34:41,919
Speaker 14: And so we've actively tracked that metric to see how

658
00:34:41,920 --> 00:34:44,960
Speaker 14: people's consumption of AI is growing over time. And you

659
00:34:45,040 --> 00:34:48,240
Speaker 14: see this happen in amazing ways. So things like Codex,

660
00:34:48,239 --> 00:34:51,560
Speaker 14: for example, we've seen grow ten x since August purely

661
00:34:51,600 --> 00:34:55,080
Speaker 14: on consumption of tokens around coding and you start to

662
00:34:55,080 --> 00:34:58,040
Speaker 14: see that same pattern emerge across multiple lanes of use

663
00:34:58,200 --> 00:35:00,600
Speaker 14: and across multiple areas of work. And that's the metric

664
00:35:00,640 --> 00:35:02,480
Speaker 14: I look at because if that number is going up

665
00:35:02,480 --> 00:35:04,600
Speaker 14: and these people are using us for more things, and that's.

666
00:35:04,440 --> 00:35:05,080
Speaker 4: The ultimate goal.

667
00:35:05,920 --> 00:35:09,480
Speaker 3: Open Aiico brad lightcap there and it is all about use.

668
00:35:09,880 --> 00:35:11,320
Speaker 3: And we got a lot of that news out of

669
00:35:11,360 --> 00:35:14,359
Speaker 3: open aistaf day. Let's down on attention to Blomberg's Rachel

670
00:35:14,400 --> 00:35:17,839
Speaker 3: mets and look, there is a lot of crossover here

671
00:35:17,880 --> 00:35:20,759
Speaker 3: of other technologies being into what twined really with the

672
00:35:20,840 --> 00:35:21,880
Speaker 3: chat gipt offering.

673
00:35:23,239 --> 00:35:24,120
Speaker 4: Yeah, exactly.

674
00:35:24,200 --> 00:35:28,200
Speaker 17: I mean just yesterday at the company's developer event, we

675
00:35:28,239 --> 00:35:31,120
Speaker 17: saw the company trying to bring in lots of different

676
00:35:31,160 --> 00:35:35,040
Speaker 17: companies applications like Zilo for instance, and you would use

677
00:35:35,080 --> 00:35:38,200
Speaker 17: it within chat GBT, and a number of other companies

678
00:35:38,239 --> 00:35:41,279
Speaker 17: as well have been building these apps and Opening I

679
00:35:41,360 --> 00:35:44,279
Speaker 17: wants all kinds of people to build these apps, and

680
00:35:44,880 --> 00:35:47,840
Speaker 17: they want to make chat gbt more of a I

681
00:35:47,840 --> 00:35:49,600
Speaker 17: guess like more of a starting point and more of

682
00:35:49,640 --> 00:35:52,919
Speaker 17: an operating system almost for a lot of different kinds

683
00:35:52,920 --> 00:35:56,080
Speaker 17: of computing things that you would normally do perhaps on

684
00:35:56,120 --> 00:35:58,799
Speaker 17: your other apps on your phone or would go straight

685
00:35:58,840 --> 00:36:02,160
Speaker 17: to a website for things like that, and like Brad said,

686
00:36:02,840 --> 00:36:05,320
Speaker 17: that will take a lot of competing power.

687
00:36:06,840 --> 00:36:09,520
Speaker 2: Rachel sam Altman and other executives took about an hour

688
00:36:09,600 --> 00:36:11,759
Speaker 2: of questions from us. You and I were hanging out

689
00:36:11,800 --> 00:36:14,480
Speaker 2: in the afternoon of dev day. There was like lots

690
00:36:14,480 --> 00:36:16,520
Speaker 2: of other news. You know, it could be the eight

691
00:36:16,640 --> 00:36:19,200
Speaker 2: hundred million weekly users. What jumped out to you? What

692
00:36:19,320 --> 00:36:23,200
Speaker 2: is it you think moved the needle, if anything, I thought.

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00:36:23,000 --> 00:36:27,839
Speaker 17: That this that eight hundred million weekly user. I mean

694
00:36:27,840 --> 00:36:30,040
Speaker 17: it was almost kind of just like mentioned as you know,

695
00:36:30,160 --> 00:36:32,319
Speaker 17: like one of a number of things. I feel like

696
00:36:32,360 --> 00:36:35,000
Speaker 17: that's really significant milestone, and it seems to have been

697
00:36:35,040 --> 00:36:38,000
Speaker 17: achieved really quickly. And I think it's just a really

698
00:36:38,080 --> 00:36:42,040
Speaker 17: putting a big signpost on the idea that CHADGBT has

699
00:36:42,760 --> 00:36:46,040
Speaker 17: just kept going. As such, it's a machine that's really

700
00:36:46,080 --> 00:36:48,880
Speaker 17: gone faster and faster and faster since it was launched

701
00:36:48,960 --> 00:36:52,840
Speaker 17: in late twenty twenty two. This is as Nick Turley,

702
00:36:52,880 --> 00:36:56,360
Speaker 17: who's the head of chad GBT said about almost a

703
00:36:56,520 --> 00:36:58,480
Speaker 17: tenth of the world's population. I mean, that is a

704
00:36:58,600 --> 00:37:00,879
Speaker 17: huge amount of adoption to have, and I think it's

705
00:37:00,920 --> 00:37:03,600
Speaker 17: really important to think about everything the company does through

706
00:37:03,600 --> 00:37:04,120
Speaker 17: that lens

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00:37:04,560 --> 00:37:07,080
Speaker 3: Ludeberg Rachel mets, fantastic to have you