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Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is a

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Speaker 1: live from Coast to coast with Caroline Hyde in New

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Speaker 1: York and Vla Loow in sentrancs go.

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Speaker 2: This is Bloomberg Tech coming up.

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Speaker 3: All lies on in video after the closing bell today,

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Speaker 3: we'll discuss investor expectations and a lot more.

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Speaker 4: Plus Anthropic loosens its central safety policy once called to

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Speaker 4: its mission and in a growing dispute with the US

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Speaker 4: Defense Department over Godrails.

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Speaker 3: And Sequoia partner Alfred Lynn joins us with the CEO

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Speaker 3: of his new portfolio company, Rose Faces, Michael Manipat.

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Speaker 4: Later this hour from private markets, we go back to

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Speaker 4: the public.

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Speaker 5: Markets that get a little bit of a reprieve.

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Speaker 4: Today, and we're at more than a percentage point on

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Speaker 4: then as that one hundred and this is as we

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Speaker 4: anticipate in video. This is as we of course digest

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Speaker 4: what was said at the State of the Union roast

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Speaker 4: into glasses is that some of the viewpoint there.

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Speaker 5: Bitcoin though at more than five percent, I mean, its

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Speaker 5: best stay since February six. What are you looking at?

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Speaker 3: I'm looking at in video, we are anticipating its earnings.

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Speaker 3: It is a high stake earnings moment for markets more broadly,

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Speaker 3: and the stocks up one point eight percent going into it. Again,

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Speaker 3: this is after the closing bell, and the expectation is

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Speaker 3: this is a sixty six billion dollar quarter, most of

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Speaker 3: that coming from data center. We're bracing because the options

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Speaker 3: market is telling us that there will be a five

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Speaker 3: percent swing in ib direction. But if you look back

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Speaker 3: at the last eight quarters, actually the reaction is typically

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Speaker 3: pretty muted, but in Vidia has fallen in at least

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Speaker 3: four out of the last six post earnings sessions. And

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Speaker 3: then there's the guidance, so to speak, intelligencing around this.

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Speaker 3: Kunjinsavani joins us with what to expect in your preview,

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Speaker 3: We think about the April quarter, the current period, and

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Speaker 3: how that's going to go. And actually what you reflect

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Speaker 3: on is if you go back to Cees that first

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Speaker 3: week of January, they kind of told us how it's going.

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Speaker 2: What are the metrics you're looking for?

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Speaker 6: Yeah, I mean, look, you are expect them to beat

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Speaker 6: by mid single to high single digits. But as you said,

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Speaker 6: you know, stock has not done much since years because

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Speaker 6: most of that goodness has already been digested and priced in,

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Speaker 6: So investors are waiting for that next big thing, which

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Speaker 6: I don't think he will drop today because remember gtc's

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Speaker 6: around the corner, so we might want to save it

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Speaker 6: for that. We are, though, looking for an upside to

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Speaker 6: that five hundred billion dollars pipeline for twenty twenty six

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Speaker 6: and any signals he can give us regarding demand spilling

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Speaker 6: into twenty twenty seven, so that will be key for investors.

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Speaker 4: Can you tell us about how much we need to

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Speaker 4: understand in terms of any potential bottlenecks with Rubin, how

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Speaker 4: we're seeing manufacturing progress.

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Speaker 5: Is there any thing he can do to alleviate concerns there?

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Speaker 6: I think he gave a lot more at CES, which

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Speaker 6: generally he does not saves it for GtC about where Rubins,

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Speaker 6: So the concerns of the hiccups and manufacturing there are

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Speaker 6: much less. The concerts are more about, you know, they

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Speaker 6: cannot deliver a lot of upside given the supply constraints,

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Speaker 6: whether it's from TSMC, whether it's from packaging, whether it's

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Speaker 6: from memory. So at this point it will be more

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Speaker 6: of a smooth sailing.

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Speaker 3: This part where the story of technology marries with their financials,

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Speaker 3: and that's probably in margins right, margins are seventy five

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Speaker 3: percent right now. One of the things you spotted last quarter,

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Speaker 3: right was the increasing proportion of content that Nvidia holds

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Speaker 3: in the server design. Used to be just the GPU,

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Speaker 3: so much more now is that where the pressure is

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Speaker 3: like seventy five percent margin maintaining that.

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Speaker 6: Yeah, the pressure is there, but they're handsomely being able

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Speaker 6: to do that, surprising to a lot of us. And

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Speaker 6: remember now they're adding more content the deal with meta

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Speaker 6: regarding the CPU, right that also will be a significantly

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Speaker 6: high margin product when you think of CPU. So they're

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Speaker 6: keeping on adding these small sockets around the GPUs which

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Speaker 6: don't bring in significant billions of dollars of revenue compared

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Speaker 6: to the GPU, but add a lot to the margin,

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Speaker 6: helping that pressure which is on the GPU margin.

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Speaker 4: Conjin Savani, it's going to be busy day. Thank you

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Speaker 4: for joining us. A Bloomberg Intelligence look. Investors are looking

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Speaker 4: to InVideo for some sort of fresh clues on the

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Speaker 4: AI market's impact. Our next guest warns the biggest to

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Speaker 4: equities is a breakdown in the AI trade. Martin Norton,

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Speaker 4: chief investment strategist and empower saying that if there's clear

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Speaker 4: evidence that AI won't be transformative as expected could undermine

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Speaker 4: a major growth engine for both the US economy and

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Speaker 4: equity markets. But at the moment, Marta, everyone's worrying that

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Speaker 4: it's too effective. The bullishness has become bearishness.

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Speaker 5: Where do you sit on that?

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Speaker 7: I mean, it feels as though when we look at AI,

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Speaker 7: everything is a loser. Investors have lost confidence in the

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Speaker 7: epicenter of the AI trade, the hyperscillers and video meta

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Speaker 7: and at the same time they're questioning how effective and

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Speaker 7: how profound AI will be in disrupting all these other industries.

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Speaker 7: So there's we're kind of in a contradictory phase when

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Speaker 7: it comes to AI. At the moment, I do think

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Speaker 7: this opens up opportunity. I think it opens up opportunity

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Speaker 7: among the AI AIA list names, and I also think

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Speaker 7: it opens up opportunity in some of these disrupted industries.

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Speaker 4: When you say opportunity, you mean start to catch the

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Speaker 4: falling nine, start to perhaps add to your investments and

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Speaker 4: companies that are beaten up.

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Speaker 2: Yes.

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Speaker 7: Absolutely, And you know, the following knife narrative is especially

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Speaker 7: important because it is a bit dangerous. We are looking

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Speaker 7: at a transformative technology and we don't exactly understand what

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Speaker 7: that terminal value looks like because we don't understand how

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Speaker 7: these business models will completely evolve. But I think if

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Speaker 7: we have a base case expectation that we're seeing AI integration,

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Speaker 7: then I think you can think of some of these

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Speaker 7: companies as maybe survivors or even thrivers.

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Speaker 3: I'm reading our markets wrap on on Bloomberg, and they're

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Speaker 3: painting a picture where if in Video earnings are really strong,

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Speaker 3: that will carry the market for the rest of the

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Speaker 3: week and maybe further afield. It will be good let's

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Speaker 3: say for then as that one hundred, But if they

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Speaker 3: are too strong, then we'll go back to the idea

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Speaker 3: that AI is coming for software as an example, you know,

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Speaker 3: there is a world where in Video's earnings are too

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Speaker 3: good and we end up with the same result, which

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Speaker 3: is anxiety about legacy sectors. Do you kind of buy that.

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Speaker 7: Argument well in terms of the day to day price

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Speaker 7: movement with how investors are going to react to Nvidio,

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Speaker 7: I think that's anyone's call. I do think there's a

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Speaker 7: thread the needle type of environment where they have to

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Speaker 7: be just right this goldilocks scenario. But I think the

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Speaker 7: real question is what can slow the disruption or the

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Speaker 7: fear investors have around disruption. And I guess I can't

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Speaker 7: point to an immediate catalyst that would make investors say, hey,

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Speaker 7: all as well with a lot of these sucks, because

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Speaker 7: what we're worrying about is not the here and now,

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Speaker 7: it's several years out.

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Speaker 2: And so that's why I.

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Speaker 7: Think when you were looking at these opportunities, we really

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Speaker 7: do have to take a longer term mindset.

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Speaker 3: Quite rightly, when the team met this morning, we were like,

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Speaker 3: there are many other earnings going on at the same time,

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Speaker 3: and you know, you reflect on this in your notes. Right,

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Speaker 3: earnings have been strong generally speaking, they've met expectations. But

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Speaker 3: in that environment, that still isn't enough. What are you

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Speaker 3: learning and aggregate in this earning season four Tech?

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Speaker 7: Well, I mean, if we're looking broadly speaking, just looking

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Speaker 7: at the economy overall, we've seen strong earnings, strong revenue growth.

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Speaker 7: I think that's a signal of fundamental health. I think

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Speaker 7: we see that in technology as well. I think we

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Speaker 7: see that with the hyperscalars. What I've been amazed by,

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Speaker 7: or maybe not amazed by, but I think it's noteworthy,

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Speaker 7: is that despite all the investor jetters around the massive

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Speaker 7: spending that we're seeing. The companies are not slowing down.

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Speaker 7: Those jitters are not disrupting their plans. In fact, they

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Speaker 7: increase estimates relative to analyst expectations for twenty twenty six

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Speaker 7: in terms of what they're going to spend on CAPEX,

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Speaker 7: and so I think, as much as we might have

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Speaker 7: jetters around this, this AI train is continuing to steam forward, steaming.

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Speaker 5: Forward, Marta.

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Speaker 4: What we've seen a lot of steam on is kind

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Speaker 4: of AI douma or dystopia. We've seen a lot of

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Speaker 4: notes put out, look some of them by the very

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Speaker 4: leaders of anthrow for example, talk about the adolescents of technology.

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Speaker 4: We've seen the Satrinian research just calls shockwaves through the market,

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Speaker 4: as some have labeled it, sort of basically completely dystopian

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Speaker 4: made up.

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Speaker 5: But in other ways, some people.

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Speaker 4: Put some real credence to potentially double digit unemployment due

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Speaker 4: to rapid agentic adoption.

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Speaker 5: How are you thinking about it?

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Speaker 7: Well, I think those notes are really powerful and a

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Speaker 7: really valuable thought exercise, and they're tapping into obviously based

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Speaker 7: on a market action they're typing, they're tapping into what

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Speaker 7: investors really fear, is that worst case scenario. We hear

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Speaker 7: it time and time again that AI is going to

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Speaker 7: destroy the labor market, and so these notes are valuable

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Speaker 7: in the sense that they put real color, they paint

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Speaker 7: a real picture to what that looks like. But I

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Speaker 7: think what we have to remember is none of us

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Speaker 7: know the future perfectly, and that's one potential outcome. But

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Speaker 7: there's a whole range of different outcomes, some of which

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Speaker 7: are a lot more positive than what these notes have suggested.

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Speaker 7: And so I think as we invest can now say, Okay,

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Speaker 7: now these evaluations are beginning to reflect some of these

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Speaker 7: more dystopian outcomes, and those are so positive outcomes that

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Speaker 7: can occur, and so that makes me as an investor,

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Speaker 7: get a little bit more excited about putting money to work.

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Speaker 3: Mardin Norton of Empower, thank you very much. Okay, take

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Speaker 3: a look at these live pictures. NASA is rolling the

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Speaker 3: Space Launch System rocket and Orion spacecraft for Artemis two

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Speaker 3: off the launch pad and back to the hangar at

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Speaker 3: the agency's Kennedy Space Center in Florida. It's only four

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Speaker 3: miles away, but the trek is expected to take up

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Speaker 3: to twelve hours. You're going to have to take my

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Speaker 3: word for it, but those are live pictures of something

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Speaker 3: that's moving at zero point three three miles per hour.

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Speaker 3: When it gets there, the team can finally start troubleshooting

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Speaker 3: the rocket's up a stage issue, and from there we

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Speaker 3: wait for NASA to confirm the next potential launch window.

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Speaker 4: Carol fascinating ed, thank you mean while coming up that

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Speaker 4: we're going to be breaking down President Trump the State

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Speaker 4: of the Union address?

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Speaker 5: What was said? What wasn't said? When it comes to ten,

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Speaker 5: this says bloomag Tech.

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Speaker 8: We're telling the major tech companies that they have the

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Speaker 8: obligation to provide for their own power needs. They can

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Speaker 8: build their own power plants as part of their factory

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Speaker 8: so that no one's prices will go up and in

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Speaker 8: many cases, prices of electricity will go down for the community.

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Speaker 3: That was President Trump during his State of the Union address,

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Speaker 3: saying his administration told major tech companies to build their

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Speaker 3: own power plants for their data centers, an announcement that

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Speaker 3: comes amid growing opposition to data center projects around the

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Speaker 3: country blamed for a jump in electricity prices.

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Speaker 2: Bloomberg TV's Washington.

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Speaker 3: Correspondent Talle Kendall joins us, now we knew that this

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Speaker 3: would be about the economy, and we were looking for

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Speaker 3: lines in the President's speech and address that they were

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Speaker 3: related to AI.

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Speaker 2: That was probably the clearest. What else do we need

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Speaker 2: to know?

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Speaker 9: Definitely, ed that was the clearest, particularly because it goes

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Speaker 9: back to the issue of affordability, which really seemed to

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Speaker 9: define President Trump's comments last night, because this push to

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Speaker 9: have big tech companies build with their own power plans

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Speaker 9: ties back to the idea that the President wants to

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Speaker 9: see those electricity costs come down for American consumers. Now,

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Speaker 9: as you mentioned, we were expecting this announcement from the President,

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Speaker 9: Bloomberg News reporting that he would roll out what's being

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Speaker 9: called a rate payer protection pledge, Though he didn't necessarily

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Speaker 9: outline additional details, including how this would be implemented or enforced.

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Speaker 9: It is our understanding this would be a non binding pact.

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Speaker 9: The people familiar with the matter do tell us here

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Speaker 9: at Bloomberg News that the White House is in active

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Speaker 9: discussions with the companies like Microsoft and Alphabet about signing

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Speaker 9: on to these pledges. We very likely could see a

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Speaker 9: more formalized effort announced by the White House next month.

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Speaker 9: Amid reports that there will be a formal White House

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Speaker 9: event here where I am as the AD Ministry is

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Speaker 9: trying to show some more forward progress. We know, for example,

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Speaker 9: officials had called just last month for the nation's largest

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Speaker 9: power grid operator, PJM, to host an emergency power auction

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Speaker 9: specifically for these big tech companies, because as we head

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Speaker 9: into the midterms, it is all about affordability and ed

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Speaker 9: and Caroline, that's really why we saw President Trump yesterday

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Speaker 9: focus more on those domestic issues set a foreign policy issues,

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Speaker 9: despite those really being the ones to dominate the headlines

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Speaker 9: here in Washington in recent weeks.

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Speaker 4: I mean, what's been dominating the minds of many big

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Speaker 4: tech CEOs and leaders has been tariffs as well, Tyler,

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Speaker 4: do we get any instinct on where that's going.

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Speaker 5: Well, that means for the cost of living.

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Speaker 9: As well, right, Caroline, I mean President Trump really did

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Speaker 9: double down on his tariff plans last night. In fact,

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Speaker 9: he threatened our trading partners with additional levies if anyone

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Speaker 9: looks to rearrange or renegotiate the trade frameworks that are

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Speaker 9: already in place. Of course, front and center in that

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Speaker 9: chamber were some of those Supreme Court justices that struck

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Speaker 9: down President Trump's broad based AIPA tariffs. Notably, though, if

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Speaker 9: you go through the transcript, President Trump did not directly

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Speaker 9: address China, which is pretty interesting considering that US China tentions,

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Speaker 9: particular around trade have really dominated this past year and

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Speaker 9: the Trump administration's policies.

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Speaker 5: In fact, it.

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Speaker 9: Marked with the first time in nearly two decades that

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Speaker 9: a president did not directly address US economic ties with

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Speaker 9: China in their State of the Union address, Ed and Caroline.

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Speaker 9: We're looking ahead, of course, to a few weeks in

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Speaker 9: April when President Trump will sit down face to face

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Speaker 9: with Chinese President Xijingping in China. Top of mind is

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Speaker 9: going to be those trade negotiations. The USTR Jamison Grierson

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Speaker 9: on Bloomberg Television earlier today that AIPA ruling will not

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Speaker 9: change our tariff calculus.

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Speaker 4: Tier Kendall, thank you so much for the breakdown there

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Speaker 4: Following the State of the Union. Now sticking with Washington Anthropic,

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Speaker 4: but it's loose to its central safety policy to keep

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Speaker 4: pace in a rapidly changing field. Now this is off

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Speaker 4: to the Pentagon threatened to invoke a Cold War era

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Speaker 4: law to compel Anthropic to allow the US military to

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Speaker 4: use the company's technology if it failed to comply with

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Speaker 4: the government's terms according to sources, I mean most seenor

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Speaker 4: Tech editor Mike Sheppan joins us, you go into the

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Speaker 4: blog that Anthropic has pointed out, and yes, they talk

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Speaker 4: about some of the steps have already been taken.

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Speaker 5: In terms of safety, some of the achievements they've.

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Speaker 4: Already made, But they really highlight that despite rapid advancements

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Speaker 4: in AI capabilities in the last three years, government action

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Speaker 4: in AI safety has been slow.

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Speaker 5: Is that what they're trying to call out here.

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Speaker 10: You know, Caro, That is one thing they're trying to

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Speaker 10: call out, But they are also acknowledging this stiff competition

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Speaker 10: that they face in the AI space globally. They are

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Speaker 10: competing with OpenAI, xai, and of course with Google for

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Speaker 10: a piece of what MARKA. Norton was also acknowledging as

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Speaker 10: a massive competitive landscape. There is so much business to

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Speaker 10: be done out there, and we have seen industry after

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Speaker 10: industry shaken by the prospect of some of these new

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Speaker 10: tools from Anthropic and from other providers that could really

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Speaker 10: change the way business is done and how people actually

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Speaker 10: do their work from day to day.

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Speaker 2: So there is both that question, but then also.

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Speaker 10: The one that you zeroed in on, and that is

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Speaker 10: that they are not seeing any traction at the federal

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Speaker 10: level when it comes to discussion of these safety oriented issues,

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Speaker 10: and of course that's the conversation coming up now at

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Speaker 10: the Pentagon. The company is insisting that it will not

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Speaker 10: be relaxing that those two standards, that it doesn't want

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Speaker 10: mass surveillance of Americans via the Pentagon through its technology

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Speaker 10: or the fully autonomous use of its technology in weapons.

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Speaker 10: But again, this relaxation of that safety principle when it

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Speaker 10: comes to competition is a significant and worthy change to

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Speaker 10: note here.

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Speaker 2: Take us inside the room.

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Speaker 3: We reported that Anthropic CEO Dari Ramaday met with Secretary

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Speaker 3: HEGXF I believe yesterday Tuesday. There is a deadline of

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Speaker 3: Friday from the Pentagon's perspective, But in our reporting, Anthropic

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Speaker 3: has conditions of its own that it is putting to

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Speaker 3: the Pentagon quickly.

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Speaker 10: Yes, Anthropic has set those conditions as no mass surveillance

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Speaker 10: and no use of its technology and fully autonomous targeting.

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Speaker 10: And now those conditions it's unclear at what point they

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Speaker 10: will heal. The Pentagon says, look, you don't need those conditions.

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Speaker 10: We will abide by the law and we do not

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Speaker 10: want and this is according to the Pentagon's own new

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Speaker 10: AI acceleration strategy released last month. They don't want companies

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Speaker 10: to attach asterisks or conditions on the use of technology

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Speaker 10: by the Pentagon if they are doing business with the

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Speaker 10: government and they have threatened the company with some dire consequences.

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Speaker 10: One is that it would use the Defense Production Act

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Speaker 10: to simply in essence, impound the technology and use it

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Speaker 10: over Anthropics objections, or failing that, they would actually declare

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Speaker 10: Anthropica's supply chain risk, and that would mean that vendors

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Speaker 10: with the would have to certify that they are not

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Speaker 10: using Anthropics technology and that we'll pose a business risk

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Speaker 10: to Dariy Armaday and his business.

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Speaker 3: Bloomberg's Mike Shephard, thank you very much. Now, coming up

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Speaker 3: on the show, we're going to speak with Circle CEO

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Speaker 3: Jeremy Alair, fresh off the company's earning school.

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Speaker 2: This is Bloomberg Tech, just.

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Speaker 4: Checking on shares Circle on the day, having their best

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Speaker 4: since June twenty twenty five. We're up twenty three percent

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Speaker 4: after the company would pulled a fourth quarter results that

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Speaker 4: top expectations. Stable cooin issue were posting both profit and

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Speaker 4: revenue growth beating analyst estimates as digital asset activity really

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Speaker 4: picked up in the late in the year. Here with

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Speaker 4: more on the results the outlook ahead of Circle CEO

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Speaker 4: Jeremy Alair. Jeremy, what's so interesting is the moon music

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Speaker 4: around crypto has been pretty.

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Speaker 5: Dre in the fourth quarter fiscal fourth quarter.

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Speaker 4: But have people in turn and using stable coin even more.

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Speaker 4: Adoption been growing because of this sort of volatility of

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Speaker 4: people in exiting bitcoin and wanting to hold USDC instead.

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Speaker 11: Well, thanks for having me on, and I would sort

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Speaker 11: of start by just saying, you know, if you look

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Speaker 11: at the arc of twenty twenty five and the success

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Speaker 11: of you know, legislative initiatives like the Genius Act, the

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Speaker 11: awareness around stable coins as a key infrastructure that can

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Speaker 11: be used in the financial system in payments and capital markets,

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Speaker 11: and the incredible growth which are obviously showing up in.

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Speaker 2: Our full year and Q four numbers.

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Speaker 11: You know, what we've seen in some respects is stable

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Speaker 11: coins as a technology as a use case, decoupling from

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Speaker 11: you know, digital asset markets, or decoupling from you know,

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Speaker 11: just you know, speculating on the price of bitcoin or

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Speaker 11: things like that. And that's something that we've believed for

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Speaker 11: a very long time is that blockchains, stable coins and

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Speaker 11: now as we see this kind of collision of this

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Speaker 11: with a capabilities and agentic computing are creating utility for

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Speaker 11: businesses and financial institutions and households and and that's that's

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Speaker 11: driving this shift. And so I think the market is

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Speaker 11: just starting to understand there are you know, internet financial

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Speaker 11: platform and infrastructure companies that are building for this new

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Speaker 11: economic system that's built around real world money like usd

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Speaker 11: C and this and blockchain technology. And then there's a

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Speaker 11: there's a different market which is certainly more speculative about

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Speaker 11: about you know, digital assets more broadly.

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Speaker 4: I mean, that's so interesting because that we've just had

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Speaker 4: the news reporting that maybe metas back on thinking about

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Speaker 4: how adoption of stable coin is going to work within

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Speaker 4: its own platform. Talk to us about how you're diversifying,

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Speaker 4: because yes, you can do a lot with stable coins

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Speaker 4: and indeed putting money into US treasury assets, But where

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Speaker 4: else for the business?

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Speaker 2: Now, well, a couple of things, you know.

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Speaker 11: I think the first is that you know, our core

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Speaker 11: business is thriving. You know, USDC grew seventy two percent

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Speaker 11: year on year, the amount of transactions happening in Q

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Speaker 11: four reached nearly twelve trillion. That's up around two hundred

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Speaker 11: and fifty percent year on year.

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Speaker 2: Our market share has grown.

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Speaker 11: We're nearly fifty percent of all stable coin transactions happening

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Speaker 11: in the world. And it's spreading, meaning it's it's the

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Speaker 11: intuits of the world. It's the JP Morgan's of the world,

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Speaker 11: it's the visas of the world, it's payroll companies, so

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Speaker 11: many companies that are there. So that is strong and growing,

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Speaker 11: and we're still in the early stages of that, but

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Speaker 11: we see the opportunity as as much larger and so

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Speaker 11: for us this to your question. You know, we're kind

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Speaker 11: of going down the stack by building operating systems for

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Speaker 11: this new economic system, operating systems that can support agentic applications,

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Speaker 11: broader financial applications through ARC. We're going up the stack

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Speaker 11: by building applications that are useful to any financial institution

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Speaker 11: that wants to plug into this and make this kind

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Speaker 11: of the pipes for how they move money.

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Speaker 2: Can you be a little bit more granular.

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Speaker 3: You talked about overachievement right in new revenue streams. Where

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Speaker 3: and how did you did you achieve that?

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Speaker 11: Yeah, so specifically in new revenue streams, we saw other

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Speaker 11: revenue which include subscriptions and services revenue includes transaction revenue.

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Speaker 11: You know, these were completely new lines of business a

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Speaker 11: year ago. In Q four of twenty four, they grew

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Speaker 11: fifteen x to thirty seven million dollars of revenue in

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Speaker 11: the quarter, and we've also given some guidance around twenty

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Speaker 11: twenty six, we see them growing you know, another fifty percent.

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Speaker 11: And so this includes you know, product and partnership work

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Speaker 11: that we do to take the stable point network technology

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Speaker 11: we have and make it available through partnerships across more

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Speaker 11: and more blockchain networks. This includes transaction fees that are

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Speaker 11: charged for different services that we offer. And so there's

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Speaker 11: a there's a mixture of of new revenue streams in there,

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Speaker 11: and we have not really yet turned on revenue from

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Speaker 11: major platforms like CPN and ARC yet, but we're you know,

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Speaker 11: we're encouraged by that growth and that's that helped our

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Speaker 11: margin as well in the quarter.

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Speaker 2: All right, Jeremy Alero circle, thank you very much. Again.

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Speaker 3: The stock really pushing higher twenty five percent, on track

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Speaker 3: for its best day since June when at iPod last year.

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Speaker 2: Coming up We're gonna have details.

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Speaker 3: Of Paramounts improved offer for Warner Brothers as both companies

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Speaker 3: actually prepare to release their earnings. A lot more to discuss.

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Speaker 3: It is halftime and this is Bloomberg Tech. Welcome back

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Speaker 3: to Bloomberg Tech. Let's take a look at shares of

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Speaker 3: Warner Bros. Discovery, paramount S, Guidance, and Netflix. Warner Brothers

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Speaker 3: Discovery softer half percentage point, the other two higher, Netflix

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Speaker 3: up five percent.

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Speaker 12: Hm.

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Speaker 3: Why the Brother's board said that Paramount's Guide answers new

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Speaker 3: thirty one dollar per share offer maybe a better deal

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Speaker 3: than its existing agreement with Netflix, but regulatory hurdles for

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Speaker 3: both bids remain. Paramount is seen by some to have

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Speaker 3: the upper hand because of the Famili's ties to President Trump.

438
00:23:18,000 --> 00:23:20,680
Speaker 3: Last night at the State of the Union address, Paramount

439
00:23:20,800 --> 00:23:24,320
Speaker 3: CEO David Ellison was a guest of Trump ally South

440
00:23:24,359 --> 00:23:27,159
Speaker 3: Carolina Senator Lindsey Graham, and I guess carry up five

441
00:23:27,160 --> 00:23:30,199
Speaker 3: percent on Netflix because remember quite a large portion of

442
00:23:30,200 --> 00:23:32,320
Speaker 3: the investor base. I think the Netflix at this juncture

443
00:23:32,520 --> 00:23:33,639
Speaker 3: should walk away.

444
00:23:33,880 --> 00:23:35,879
Speaker 4: And they get a nice bit of money if they do,

445
00:23:35,960 --> 00:23:40,000
Speaker 4: potentially being financed by that. Mister Ellison let's move away

446
00:23:40,000 --> 00:23:41,560
Speaker 4: from the politics of it all, but get into the

447
00:23:41,600 --> 00:23:42,760
Speaker 4: real details of the offer.

448
00:23:42,760 --> 00:23:44,520
Speaker 5: Bluemore Media reporters Hannah Mina.

449
00:23:44,440 --> 00:23:47,200
Speaker 4: Is with us as sag and continues, and the may

450
00:23:47,800 --> 00:23:50,199
Speaker 4: is a question mark here. Basically, thirty one dollars is

451
00:23:50,200 --> 00:23:53,760
Speaker 4: good enough to reopen those negotiations that got so intense

452
00:23:53,800 --> 00:23:55,640
Speaker 4: that at midnight they were being forced to put down

453
00:23:55,680 --> 00:23:56,080
Speaker 4: the phone.

454
00:23:56,359 --> 00:23:58,280
Speaker 13: Yeah, and just to be clear, you know, the Warner

455
00:23:58,320 --> 00:24:01,760
Speaker 13: Brothers board has not, you know, called this new offer superior.

456
00:24:02,240 --> 00:24:05,719
Speaker 13: It has just met the threshold for further talks. If

457
00:24:05,760 --> 00:24:08,240
Speaker 13: they do end up backing the offer, then Netflix has

458
00:24:08,240 --> 00:24:09,360
Speaker 13: four days to respond.

459
00:24:10,840 --> 00:24:14,640
Speaker 3: We are in a slightly unusual situation where both Warner

460
00:24:14,640 --> 00:24:17,960
Speaker 3: Brothers Discovery and Paramounts Guidance will report earnings, and I

461
00:24:17,960 --> 00:24:20,840
Speaker 3: guess we'll kind of learn how it's going for both,

462
00:24:20,960 --> 00:24:24,159
Speaker 3: you know, Paramount of Particular Interest Sunday and Night of

463
00:24:24,200 --> 00:24:25,080
Speaker 3: the Seven Kingdoms.

464
00:24:25,119 --> 00:24:26,639
Speaker 2: That's what I was doing on my couch.

465
00:24:27,080 --> 00:24:30,200
Speaker 3: It's one example of where like it's going. Well, maybe

466
00:24:30,760 --> 00:24:33,600
Speaker 3: what do we expect to hear about the health of

467
00:24:33,640 --> 00:24:35,760
Speaker 3: the business pre any merger?

468
00:24:36,400 --> 00:24:39,520
Speaker 13: Yeah, I mean for Paramount, which we'll hear about their

469
00:24:39,560 --> 00:24:40,160
Speaker 13: earnings later.

470
00:24:40,200 --> 00:24:40,640
Speaker 2: Today.

471
00:24:41,480 --> 00:24:45,160
Speaker 13: You know, we're expecting a strong finish for twenty twenty five.

472
00:24:46,040 --> 00:24:49,640
Speaker 13: We're also looking to hear more about their box office plans.

473
00:24:49,720 --> 00:24:53,600
Speaker 13: They've made this commitment to produce fifteen films a year

474
00:24:53,840 --> 00:24:57,840
Speaker 13: and increase that output. For Warner Brothers, you know, they've

475
00:24:57,880 --> 00:25:00,360
Speaker 13: had you know, some content success. I'm also a fan

476
00:25:00,440 --> 00:25:03,840
Speaker 13: of a Night of the Seven Kingdoms, right, But again

477
00:25:03,960 --> 00:25:09,080
Speaker 13: for both companies, you know, we've seen cable advertising really decrease.

478
00:25:10,040 --> 00:25:13,480
Speaker 13: You know, there's still a lot of talk about how

479
00:25:13,600 --> 00:25:17,480
Speaker 13: cable television is dying. So you know, those are factors

480
00:25:17,480 --> 00:25:19,679
Speaker 13: that are going to come up on both earnings calls.

481
00:25:20,160 --> 00:25:22,359
Speaker 4: What's interesting is, if we're going back to the actual

482
00:25:22,440 --> 00:25:24,600
Speaker 4: deal part of all of this, there are a lot

483
00:25:24,640 --> 00:25:28,280
Speaker 4: of sweetness coming from Paramount's guidance, like the ticking fee.

484
00:25:28,320 --> 00:25:29,720
Speaker 5: If the regulators don't approve it.

485
00:25:29,720 --> 00:25:32,639
Speaker 4: Quickly enough, but also if the cable assets do deteriorate,

486
00:25:32,960 --> 00:25:35,159
Speaker 4: they can't walk away from it. How are you seeing

487
00:25:35,200 --> 00:25:37,000
Speaker 4: some of the nuance in the deal making here?

488
00:25:37,240 --> 00:25:40,440
Speaker 13: Yeah, Well, it's really interesting with Netflix, you know, they

489
00:25:40,440 --> 00:25:43,040
Speaker 13: only want the streaming in the studio's business, and Warner

490
00:25:43,040 --> 00:25:45,920
Speaker 13: Brothers would move forward with spinning off its cable channels

491
00:25:45,960 --> 00:25:50,480
Speaker 13: like CNN, TNT into a separate company and Netflix would

492
00:25:50,520 --> 00:25:54,560
Speaker 13: just you know, get those really strong assets. If Paramount wins,

493
00:25:54,600 --> 00:25:57,000
Speaker 13: they get everything, and they're going to have, you know,

494
00:25:57,480 --> 00:26:01,439
Speaker 13: even more to deal with with television. They're going to

495
00:26:01,480 --> 00:26:05,400
Speaker 13: have CNN under the same roof as CBS, and it'll

496
00:26:05,440 --> 00:26:07,639
Speaker 13: be really interesting to see how that plays out, how

497
00:26:07,640 --> 00:26:11,040
Speaker 13: they balance those things and really face the obstacles that

498
00:26:11,359 --> 00:26:13,280
Speaker 13: are within cable television right now.

499
00:26:14,359 --> 00:26:18,000
Speaker 3: Bloomberg's Hannah Miller, thank you very much. Elsewhere in earning

500
00:26:18,040 --> 00:26:21,639
Speaker 3: Snowflake and Salesforce report after the Bell, investors have been

501
00:26:21,680 --> 00:26:23,320
Speaker 3: dumping software stocks amid.

502
00:26:23,160 --> 00:26:24,320
Speaker 2: The AI scare trade.

503
00:26:24,520 --> 00:26:27,560
Speaker 3: Let's get the preview, Bloomberg's Brady Ford, who covers both companies.

504
00:26:27,560 --> 00:26:30,760
Speaker 3: I mean, in Salesforce's case, the expectation is like top

505
00:26:30,800 --> 00:26:33,679
Speaker 3: line growth twelve percent, which is pretty good compared to

506
00:26:33,720 --> 00:26:37,880
Speaker 3: prior quarters. It takes into account the Informatica acquisition, right,

507
00:26:37,920 --> 00:26:40,520
Speaker 3: So under the hood, what's the story that you're kind

508
00:26:40,520 --> 00:26:42,520
Speaker 3: of looking for with Salesforce?

509
00:26:43,080 --> 00:26:46,359
Speaker 14: If you ask most investors, that number doesn't look so

510
00:26:46,440 --> 00:26:48,600
Speaker 14: good because that first you think, wow, that growth rate

511
00:26:48,640 --> 00:26:51,119
Speaker 14: went up, But it's mostly the inorganic and That's what

512
00:26:51,240 --> 00:26:56,520
Speaker 14: everybody's always saidled Salesforce, that the core businesses are slowing down,

513
00:26:56,560 --> 00:26:59,800
Speaker 14: and that's the fear. Right now, it's a similar story

514
00:26:59,840 --> 00:27:03,200
Speaker 14: of are both Salesforce and Snowflake and that the big

515
00:27:03,280 --> 00:27:07,679
Speaker 14: question is are their new AI products adding new revenue?

516
00:27:08,280 --> 00:27:10,679
Speaker 14: Thus far, it's not been super clear that there's an

517
00:27:10,720 --> 00:27:13,760
Speaker 14: acceleration happening there, and so that's pretty much all people

518
00:27:13,880 --> 00:27:15,320
Speaker 14: want to hear at this point.

519
00:27:15,760 --> 00:27:18,280
Speaker 5: How much can they disprove a negative here?

520
00:27:18,840 --> 00:27:24,119
Speaker 4: What sort of line of attack really are the CEO

521
00:27:24,240 --> 00:27:26,120
Speaker 4: is going to take care to try and fend off

522
00:27:26,160 --> 00:27:29,240
Speaker 4: the idea that AI is coming for them.

523
00:27:30,040 --> 00:27:34,119
Speaker 14: We've seen CEOs getting pretty creative in their earnings call scripts.

524
00:27:34,280 --> 00:27:37,360
Speaker 14: The last couple of earnings, you know, last night, Workday,

525
00:27:37,520 --> 00:27:40,240
Speaker 14: he kind of gave you some colorful lines about how

526
00:27:40,240 --> 00:27:42,639
Speaker 14: people think Anthropic is going to replace us, but actually

527
00:27:42,640 --> 00:27:46,800
Speaker 14: Anthroptic uses our software, and so Mark Benioff tonight, certainly

528
00:27:46,840 --> 00:27:49,800
Speaker 14: I would expect some zingers about how software isn't dead.

529
00:27:50,560 --> 00:27:53,520
Speaker 14: So far Wall Street has not been convinced. No matter

530
00:27:53,560 --> 00:27:54,640
Speaker 14: how colorful.

531
00:27:54,320 --> 00:27:57,280
Speaker 4: Language, always love a bit of colorful language. You have

532
00:27:57,359 --> 00:27:58,200
Speaker 4: lots of it ready.

533
00:27:58,200 --> 00:27:58,480
Speaker 5: Ford.

534
00:27:58,560 --> 00:28:01,720
Speaker 4: We appreciate you, Thank you, thank you switching gears. The

535
00:28:01,760 --> 00:28:04,399
Speaker 4: CEO of UK self driving company Wave see what we

536
00:28:04,400 --> 00:28:07,040
Speaker 4: did there, has been telling Bloomberg Tech Europe's Tom McKenzie

537
00:28:07,200 --> 00:28:10,280
Speaker 4: about its plans to mass produce robotaxis and to roll

538
00:28:10,359 --> 00:28:12,760
Speaker 4: Wave is going to play in that market.

539
00:28:12,800 --> 00:28:16,440
Speaker 15: Take you listen, how do you mess manufacture these robotaxis?

540
00:28:16,800 --> 00:28:19,919
Speaker 15: I mean we're again, we're not retrofitting, which is capital

541
00:28:19,960 --> 00:28:23,160
Speaker 15: intensive and slow. We've got a high margin software licensing

542
00:28:23,200 --> 00:28:25,960
Speaker 15: business that works with the very largest manufacturers in the world,

543
00:28:26,359 --> 00:28:27,679
Speaker 15: and so I think these are the questions to be

544
00:28:27,680 --> 00:28:30,840
Speaker 15: asking about how this technology scales because the KPIs are

545
00:28:30,840 --> 00:28:33,000
Speaker 15: going to come the rate that our AI is learning

546
00:28:33,000 --> 00:28:36,440
Speaker 15: and increasing and performance is only accelerating with the more

547
00:28:36,520 --> 00:28:37,320
Speaker 15: deployment expansion.

548
00:28:37,600 --> 00:28:40,280
Speaker 16: To your point, this is a competition about which technology

549
00:28:40,280 --> 00:28:43,200
Speaker 16: stack works best, and you're you're throwing shade on Weiymo

550
00:28:43,440 --> 00:28:46,640
Speaker 16: with that last answer. How much of a competitive threat

551
00:28:46,680 --> 00:28:50,200
Speaker 16: is Weymo They start testing later this year and a

552
00:28:50,320 --> 00:28:52,000
Speaker 16: rollout late this year in London.

553
00:28:52,440 --> 00:28:55,640
Speaker 15: Well, I think competition is healthy and we're really excited

554
00:28:55,640 --> 00:28:57,280
Speaker 15: to see our products go head to hit. I think

555
00:28:57,320 --> 00:28:59,920
Speaker 15: it's going to be wonderful for consumers in our industry.

556
00:28:59,920 --> 00:29:02,920
Speaker 15: But it's a isn't there an amazing spot to be

557
00:29:03,000 --> 00:29:04,880
Speaker 15: in after a decade of building this that now we

558
00:29:04,960 --> 00:29:07,320
Speaker 15: have some some viable approaches here.

559
00:29:07,400 --> 00:29:10,120
Speaker 16: So you've also made that this is a software first approach.

560
00:29:10,400 --> 00:29:12,240
Speaker 2: We've seen a massive sell off in.

561
00:29:12,240 --> 00:29:15,120
Speaker 16: Software stocks as a result of the destruction from AI.

562
00:29:15,840 --> 00:29:17,680
Speaker 16: Has that led to any questioning that that is the

563
00:29:17,760 --> 00:29:20,840
Speaker 16: right approach? Have you had any investors putting pressure on

564
00:29:20,880 --> 00:29:24,080
Speaker 16: in terms of proving that you can be generating recurring

565
00:29:24,120 --> 00:29:25,640
Speaker 16: revenue and profitability.

566
00:29:26,040 --> 00:29:29,320
Speaker 15: I don't think anyone is questioning that autonomy is going

567
00:29:29,360 --> 00:29:31,080
Speaker 15: to be in every vehicle in the future. I think

568
00:29:31,120 --> 00:29:34,560
Speaker 15: that's very clear to the arket. Now every vehicle is

569
00:29:34,560 --> 00:29:36,480
Speaker 15: going to be autonomous. The question is what is the

570
00:29:36,560 --> 00:29:39,200
Speaker 15: right technology strategy and what is the right business model.

571
00:29:39,000 --> 00:29:40,240
Speaker 16: And you'll have pricing power.

572
00:29:40,520 --> 00:29:45,240
Speaker 3: One that was Wave CEO Alex Kendall speaking with Bloomberg

573
00:29:45,280 --> 00:29:48,520
Speaker 3: text Tom McKenzie. Check out more of Bloomberg Tech Europe

574
00:29:48,600 --> 00:29:51,680
Speaker 3: on the Bloomberg terminal and online. Okay, coming out, we're

575
00:29:51,680 --> 00:29:53,880
Speaker 3: going to speak to Sequoia partner Alfred Lynn, who joins

576
00:29:53,960 --> 00:29:57,520
Speaker 3: us with the CEO of his new portfolio company, Row Spaces.

577
00:29:57,840 --> 00:30:20,640
Speaker 3: Michael Manipat list next Tech. Rose Face and an AI

578
00:30:20,760 --> 00:30:24,080
Speaker 3: startup designed to help financial services firms make better use

579
00:30:24,080 --> 00:30:27,240
Speaker 3: of their own data, has launched today fifty million dollars

580
00:30:27,280 --> 00:30:30,280
Speaker 3: in seed in Series A funding led by Sequoya, Michael

581
00:30:30,320 --> 00:30:33,040
Speaker 3: manipat Sea of rose Face and Alfred Linn partner.

582
00:30:33,120 --> 00:30:35,560
Speaker 2: Is Koya are here with us. I think I'll start

583
00:30:35,560 --> 00:30:35,680
Speaker 2: with you.

584
00:30:35,720 --> 00:30:37,920
Speaker 3: If you go back to twenty twenty two, to the

585
00:30:38,000 --> 00:30:40,400
Speaker 3: chat GPT moment and you tried to do that with

586
00:30:40,480 --> 00:30:43,160
Speaker 3: the tool of the time, the limiting factor would have

587
00:30:43,160 --> 00:30:45,160
Speaker 3: been data and it would have been context.

588
00:30:45,200 --> 00:30:47,160
Speaker 2: Yes, I guess the best place.

589
00:30:46,920 --> 00:30:49,240
Speaker 3: That started to ask what you've solved for, What the

590
00:30:49,240 --> 00:30:52,960
Speaker 3: actual technology is that you've worked on that allows financial

591
00:30:53,000 --> 00:30:55,800
Speaker 3: services outfits to do better with what they've got.

592
00:30:56,160 --> 00:30:57,800
Speaker 2: Yeah, so I can start from the beginning.

593
00:30:58,240 --> 00:31:01,640
Speaker 17: Roast Space is an iiplad form for asset managers. We

594
00:31:01,720 --> 00:31:04,880
Speaker 17: help our customers use what we call their institutional memory,

595
00:31:05,200 --> 00:31:08,600
Speaker 17: all of that proprietary data and the accumulated judgment to

596
00:31:08,680 --> 00:31:12,200
Speaker 17: make better and faster decisions. As you noted, all of

597
00:31:12,200 --> 00:31:15,040
Speaker 17: our customers have had the sentiment of there is enormous

598
00:31:15,200 --> 00:31:17,800
Speaker 17: value in our data if only we can take advantage

599
00:31:17,840 --> 00:31:20,040
Speaker 17: of that. So we help them do that. So rows

600
00:31:20,080 --> 00:31:23,000
Speaker 17: space connects to all of their data systems. That's not

601
00:31:23,040 --> 00:31:26,360
Speaker 17: just documents, but it's things like accounting, trade and position

602
00:31:26,480 --> 00:31:30,640
Speaker 17: information CRMs, anything you can imagine. And our AI agents

603
00:31:30,800 --> 00:31:35,200
Speaker 17: understand the data, the connections, the inconsistencies, the conflicts, so

604
00:31:35,320 --> 00:31:38,640
Speaker 17: we can reason holistically and rigorously over all of that data.

605
00:31:38,760 --> 00:31:40,440
Speaker 2: So I can give you one quick example, so we

606
00:31:40,480 --> 00:31:41,440
Speaker 2: can more concrete.

607
00:31:41,600 --> 00:31:44,120
Speaker 17: So we're lucky to work with one of the world's

608
00:31:44,160 --> 00:31:46,800
Speaker 17: the largest credit originators and when they have a question

609
00:31:46,800 --> 00:31:50,880
Speaker 17: from them, you can imagine the compliance credit requirements of

610
00:31:51,520 --> 00:31:55,680
Speaker 17: our customers. But they're considering what trade can and should

611
00:31:55,680 --> 00:31:58,760
Speaker 17: we make. Now that involves exporting reports from a variety

612
00:31:58,800 --> 00:32:02,040
Speaker 17: of systems, reconcs in the data, cross referencing with kind

613
00:32:02,080 --> 00:32:04,920
Speaker 17: of documents. It's really easy to miss the piece of

614
00:32:05,000 --> 00:32:07,720
Speaker 17: data that might drive a key decision, right we help

615
00:32:07,760 --> 00:32:11,200
Speaker 17: give our customers that complete view with AI. You know,

616
00:32:11,360 --> 00:32:14,320
Speaker 17: it's it's the moment of agents right now. People are

617
00:32:14,400 --> 00:32:16,760
Speaker 17: so excited by agents, but really agents are only as

618
00:32:16,760 --> 00:32:18,200
Speaker 17: good as data they operate on.

619
00:32:18,840 --> 00:32:21,840
Speaker 3: Alfred, you know, Sequoia is in open AI and in

620
00:32:21,880 --> 00:32:26,560
Speaker 3: an anthropic This is the application of the environment that

621
00:32:26,600 --> 00:32:30,040
Speaker 3: we're in particularly you know relevant to audience financial services,

622
00:32:30,440 --> 00:32:34,320
Speaker 3: you know why you decided to make this particular investment

623
00:32:34,480 --> 00:32:37,240
Speaker 3: and your sort of thesis around it.

624
00:32:37,480 --> 00:32:40,720
Speaker 12: Well, we're at Sequoia where we're we first start with

625
00:32:40,720 --> 00:32:44,560
Speaker 12: the founders, founder focus, and then market driven, and this

626
00:32:44,640 --> 00:32:49,000
Speaker 12: is a place where both are just exceptional. Michael and

627
00:32:49,040 --> 00:32:51,520
Speaker 12: Ebo his co founder, they met at M and T.

628
00:32:51,720 --> 00:32:54,440
Speaker 12: They've been working together for a period of time. They

629
00:32:54,480 --> 00:32:57,080
Speaker 12: took different paths. They knew each other when they were young,

630
00:32:57,640 --> 00:33:02,560
Speaker 12: and Michael worked at Stripe Ocean. He understands the problem.

631
00:33:02,760 --> 00:33:06,160
Speaker 12: Ebo worked at in finance leadership, so he understands the

632
00:33:06,200 --> 00:33:08,960
Speaker 12: problem of taking data from all these disparate systems and

633
00:33:09,000 --> 00:33:11,880
Speaker 12: bring it all together. And so these two are attacking

634
00:33:12,000 --> 00:33:14,840
Speaker 12: a very very important problem. This is not something you

635
00:33:14,880 --> 00:33:18,080
Speaker 12: can get wrong. People use roast space to make better

636
00:33:18,160 --> 00:33:21,320
Speaker 12: decisions with AI, and they need to make sure the

637
00:33:21,400 --> 00:33:25,080
Speaker 12: numbers are right. And in many of these cases they're

638
00:33:25,120 --> 00:33:27,880
Speaker 12: making decisions to make more money. And so the investment

639
00:33:27,920 --> 00:33:30,920
Speaker 12: thesis here is we can help people make better decisions.

640
00:33:31,280 --> 00:33:33,440
Speaker 12: This is going to be a really really powerful application.

641
00:33:33,800 --> 00:33:34,080
Speaker 2: Michael.

642
00:33:34,120 --> 00:33:36,600
Speaker 4: It's interesting though, I spoke to Thrive Capital before and

643
00:33:36,680 --> 00:33:40,400
Speaker 4: they've basically built this themselves, using all their own internal emails,

644
00:33:40,480 --> 00:33:43,400
Speaker 4: change data they've built it, and probably using open AIS technology.

645
00:33:43,400 --> 00:33:44,640
Speaker 5: And I'm interested as to.

646
00:33:45,000 --> 00:33:49,280
Speaker 4: What the cutback is to the idea that anthropic plugin

647
00:33:49,400 --> 00:33:51,800
Speaker 4: isn't eventually going to be as good or businesses can't

648
00:33:51,840 --> 00:33:53,520
Speaker 4: build it themselves in some way.

649
00:33:54,640 --> 00:33:57,080
Speaker 2: It's a great question. A few things here.

650
00:33:57,640 --> 00:33:59,840
Speaker 17: First, are we used that the products in market right

651
00:33:59,880 --> 00:34:04,240
Speaker 17: now now are really focused on time savings, faster decks,

652
00:34:04,360 --> 00:34:08,720
Speaker 17: faster models. That's really valuable and it's important. Our focus,

653
00:34:08,719 --> 00:34:11,080
Speaker 17: as Alfred mentioned, is really how do we help our

654
00:34:11,120 --> 00:34:15,640
Speaker 17: customers make better decisions? And this demand's going incredibly deep

655
00:34:15,680 --> 00:34:21,200
Speaker 17: into their data, all of the records from their trades, positions, memos,

656
00:34:21,280 --> 00:34:23,760
Speaker 17: all of that. It needs to be understood in advance.

657
00:34:23,920 --> 00:34:28,240
Speaker 17: And this is an incredibly challenging problem. It's an infrastructure problem,

658
00:34:28,360 --> 00:34:31,440
Speaker 17: it is a security problem, it is a product problem,

659
00:34:31,520 --> 00:34:33,759
Speaker 17: and of course it's an AI one and that is

660
00:34:33,760 --> 00:34:36,359
Speaker 17: a problem that our Roasts based team is really well

661
00:34:36,400 --> 00:34:40,640
Speaker 17: stated to handle. There are so many nuances in finance.

662
00:34:40,840 --> 00:34:42,080
Speaker 17: How do you do reconciliation?

663
00:34:42,440 --> 00:34:44,239
Speaker 2: How do you understand what our restatement is?

664
00:34:44,680 --> 00:34:46,759
Speaker 17: What version of IBADAD do you even use in this

665
00:34:46,880 --> 00:34:49,319
Speaker 17: model and what version of the document is the correct one?

666
00:34:49,640 --> 00:34:52,520
Speaker 17: Those are all things that we care about in extreme details.

667
00:34:53,480 --> 00:34:54,920
Speaker 17: Is an adjusted has approved all that?

668
00:34:55,160 --> 00:34:56,520
Speaker 5: Yes, extreme detail.

669
00:34:56,920 --> 00:34:59,600
Speaker 4: Let's get though a little bit birds eye perspective from

670
00:34:59,600 --> 00:35:01,640
Speaker 4: a moment if we can, Alfred, because this is a

671
00:35:01,680 --> 00:35:05,560
Speaker 4: week in which we are throwing ourselves into a dystopian future.

672
00:35:05,600 --> 00:35:07,800
Speaker 4: We are trying and think what the future of Agenda

673
00:35:07,840 --> 00:35:10,799
Speaker 4: KI means for an economy, for workplace, for unemployment and

674
00:35:10,840 --> 00:35:13,040
Speaker 4: after what do you make of like the Satrini research,

675
00:35:13,080 --> 00:35:15,600
Speaker 4: what do you make of the Harvard piece about actually

676
00:35:15,800 --> 00:35:18,480
Speaker 4: the outperformance does come from human Still AI hasn't been

677
00:35:18,480 --> 00:35:21,120
Speaker 4: able to replicate that. Where do you sit in terms

678
00:35:21,160 --> 00:35:23,200
Speaker 4: of where we are in terms of GENDKI and the

679
00:35:23,239 --> 00:35:25,360
Speaker 4: impact it has on your line of business online?

680
00:35:27,040 --> 00:35:30,680
Speaker 12: So at the choir, we've always been optimist, and I

681
00:35:30,680 --> 00:35:33,760
Speaker 12: think we need to be to build the help build

682
00:35:34,480 --> 00:35:37,600
Speaker 12: legendary companies with the daring that are that we back,

683
00:35:37,680 --> 00:35:40,000
Speaker 12: and the people that are daring are people like Michael

684
00:35:40,560 --> 00:35:43,520
Speaker 12: and you know, we can think of the world as

685
00:35:43,520 --> 00:35:45,960
Speaker 12: a dystopian world. But at the same time, we just

686
00:35:46,080 --> 00:35:49,240
Speaker 12: are very very optimistic that the impacts are real. AI

687
00:35:49,320 --> 00:35:53,040
Speaker 12: impacts are real. They're going to allow us to do

688
00:35:53,480 --> 00:35:55,640
Speaker 12: a lot more than we used to be able to do.

689
00:35:55,960 --> 00:35:59,200
Speaker 2: And so yes, some of the things that we did.

690
00:35:58,960 --> 00:36:01,799
Speaker 12: Before we're going to not do anymore because it's going

691
00:36:01,840 --> 00:36:04,879
Speaker 12: to get automated by AI. But it just leads all

692
00:36:04,920 --> 00:36:08,120
Speaker 12: of us to be able to do much more strategic work,

693
00:36:08,200 --> 00:36:12,480
Speaker 12: much more creative work, and much more human work. This

694
00:36:12,640 --> 00:36:17,040
Speaker 12: is why in road Space's sort of example, there's still

695
00:36:17,040 --> 00:36:19,800
Speaker 12: a human in the loop, and we want the human

696
00:36:19,920 --> 00:36:22,839
Speaker 12: to be in the loop to make the decisions on

697
00:36:22,880 --> 00:36:23,520
Speaker 12: our behalf.

698
00:36:23,960 --> 00:36:25,000
Speaker 2: I don't think we're going to.

699
00:36:25,200 --> 00:36:28,439
Speaker 12: Give our decisions willy nilly to an AI to make

700
00:36:29,120 --> 00:36:33,880
Speaker 12: on retirements and benefits and insurance or anything related to

701
00:36:34,360 --> 00:36:37,680
Speaker 12: the type of your viewers who are thinking about those decisions.

702
00:36:38,080 --> 00:36:40,880
Speaker 3: Alfred, you named as co steward of the firm in

703
00:36:40,920 --> 00:36:42,600
Speaker 3: November alongside Pat Grady.

704
00:36:42,920 --> 00:36:45,320
Speaker 2: But interesting, you know, in leading this round.

705
00:36:45,040 --> 00:36:48,799
Speaker 3: With Sequoia, how's that first few months been, you know,

706
00:36:48,840 --> 00:36:52,800
Speaker 3: continuing to make investments, do things differently, all the same

707
00:36:52,800 --> 00:36:53,279
Speaker 3: at the firm.

708
00:36:53,320 --> 00:36:54,160
Speaker 2: Tell us what it's like.

709
00:36:54,440 --> 00:36:57,840
Speaker 12: It's pretty much been pretty smooth. It's been great working

710
00:36:57,880 --> 00:37:00,880
Speaker 12: with Pat. And the reason that we're co is because

711
00:37:00,920 --> 00:37:03,839
Speaker 12: that allows us to stay on the field, and we

712
00:37:03,920 --> 00:37:07,440
Speaker 12: love investing at Sequoia, and so we believe that that's

713
00:37:07,520 --> 00:37:10,319
Speaker 12: where most of the time should be spent. I spent

714
00:37:10,400 --> 00:37:13,440
Speaker 12: a lot of time with Michael because it's fun, it's interesting.

715
00:37:13,640 --> 00:37:15,600
Speaker 12: We get to help founders build the future.

716
00:37:16,040 --> 00:37:18,520
Speaker 3: This is a combined Seed Series A, but it's a

717
00:37:18,520 --> 00:37:22,439
Speaker 3: big chunk of change fifty million dollars. You know, when

718
00:37:22,480 --> 00:37:24,040
Speaker 3: we were talking about keeping a human in the loop,

719
00:37:24,040 --> 00:37:27,440
Speaker 3: I was immediately thinking about observability, But really I think

720
00:37:27,480 --> 00:37:28,759
Speaker 3: what we should get to is how you're going to

721
00:37:28,800 --> 00:37:31,960
Speaker 3: run this business, who you need to hire, and what

722
00:37:32,000 --> 00:37:34,759
Speaker 3: the kind of operating challenges in the near term.

723
00:37:35,200 --> 00:37:37,719
Speaker 17: Yeah, like I mentioned, this is a problem that is

724
00:37:37,760 --> 00:37:41,200
Speaker 17: not just an AI modeling one. We have to deploy

725
00:37:41,280 --> 00:37:43,360
Speaker 17: securely in our customers and environment so we keep the

726
00:37:43,440 --> 00:37:46,279
Speaker 17: data where it is. That is an infrastructure and a

727
00:37:46,320 --> 00:37:49,560
Speaker 17: security engineering challenge, and we are beating of the team there.

728
00:37:50,040 --> 00:37:52,200
Speaker 17: There is all this applied AI research that we have

729
00:37:52,280 --> 00:37:55,480
Speaker 17: to do to make sure our agents can understand arbitrary

730
00:37:56,360 --> 00:37:59,879
Speaker 17: financial data reason about it carefully. We're expanding our team

731
00:38:00,080 --> 00:38:01,920
Speaker 17: both Tan Francisco and New York. So this is a

732
00:38:02,040 --> 00:38:04,560
Speaker 17: huge year for growth for us. We expect to triple,

733
00:38:04,600 --> 00:38:06,920
Speaker 17: if not quadruple the team over both locations.

734
00:38:07,640 --> 00:38:10,960
Speaker 5: This could be a huge year, Alfred. Five pos.

735
00:38:11,040 --> 00:38:14,640
Speaker 4: And for companies that you're invested in, I think of Anthropic,

736
00:38:14,680 --> 00:38:16,920
Speaker 4: I think of open AI. It seems as though Stripe,

737
00:38:16,920 --> 00:38:18,600
Speaker 4: which you're invested in, is going to be holding off

738
00:38:18,600 --> 00:38:20,840
Speaker 4: for a little bit longer. But Alfred, where's your optimism?

739
00:38:20,880 --> 00:38:22,680
Speaker 4: There is twenty twenty sixth the year.

740
00:38:24,440 --> 00:38:25,399
Speaker 2: We're each year.

741
00:38:26,239 --> 00:38:29,319
Speaker 12: It's a funny question because each we try to make

742
00:38:29,360 --> 00:38:31,520
Speaker 12: each year better than the previous year at Sequoia, and

743
00:38:32,480 --> 00:38:35,080
Speaker 12: if you do that, every year is just we're just

744
00:38:35,160 --> 00:38:36,759
Speaker 12: that's the reason why we're out to this sick and

745
00:38:36,840 --> 00:38:39,239
Speaker 12: this year it will be I'm sure it's going to

746
00:38:39,280 --> 00:38:42,399
Speaker 12: be better than last year. And we don't really think

747
00:38:42,400 --> 00:38:46,399
Speaker 12: about the companies that are exiting. We're staying private. The

748
00:38:46,480 --> 00:38:51,640
Speaker 12: companies that last, they're in this journey and they are

749
00:38:51,800 --> 00:38:54,120
Speaker 12: on their they're working on their visions.

750
00:38:54,280 --> 00:38:55,240
Speaker 2: Yeah, for decades.

751
00:38:55,680 --> 00:38:58,680
Speaker 12: And so you know, you have Jenson who is going

752
00:38:58,760 --> 00:39:02,120
Speaker 12: to report today we've we seated that company. It's been

753
00:39:02,160 --> 00:39:05,320
Speaker 12: three decades and he's still going.

754
00:39:05,640 --> 00:39:07,480
Speaker 5: What is your optimism, Alfred?

755
00:39:08,160 --> 00:39:10,000
Speaker 4: On companies like Snowflake that you've been in for a

756
00:39:10,080 --> 00:39:12,520
Speaker 4: very long time on their ability to take on this

757
00:39:12,600 --> 00:39:15,360
Speaker 4: moment of reckoning and software. On this moment of reckoning

758
00:39:15,400 --> 00:39:18,080
Speaker 4: and disruption. Can they rebuild from within? Can they be

759
00:39:18,120 --> 00:39:20,400
Speaker 4: the ones that survive what many feel is going to

760
00:39:20,440 --> 00:39:21,440
Speaker 4: be ultimate disruption?

761
00:39:23,000 --> 00:39:25,759
Speaker 12: Well, I think the sort of fun that we have

762
00:39:25,960 --> 00:39:28,480
Speaker 12: is that at Sequoia is that we get to back

763
00:39:28,520 --> 00:39:32,440
Speaker 12: the daring build legendary companies, and so every company will

764
00:39:32,480 --> 00:39:37,120
Speaker 12: go through these ups and downs. Roast Space is an

765
00:39:37,200 --> 00:39:39,600
Speaker 12: AI native company and so they're focused on building the

766
00:39:39,600 --> 00:39:41,440
Speaker 12: way that software is built today.

767
00:39:41,760 --> 00:39:44,520
Speaker 2: Let's not forget AI is a lot of software.

768
00:39:45,800 --> 00:39:49,680
Speaker 12: The legacy software companies you know of yesteryear, like Oracle,

769
00:39:49,760 --> 00:39:52,799
Speaker 12: still exists today. Snowflake has to make the transition from

770
00:39:52,840 --> 00:39:57,000
Speaker 12: where it is today, which has lots of customers and

771
00:39:57,120 --> 00:40:01,600
Speaker 12: lots of people using it, to build more AI into

772
00:40:01,640 --> 00:40:04,879
Speaker 12: their business. If they do, they will do extremely well.

773
00:40:05,400 --> 00:40:08,520
Speaker 12: And I believe in the management team of Snowflake to

774
00:40:08,560 --> 00:40:09,760
Speaker 12: be able to make that transition.

775
00:40:10,480 --> 00:40:12,960
Speaker 5: Certainly. The CEO comes from an AI startup.

776
00:40:13,320 --> 00:40:17,360
Speaker 4: Alfred Lynn, partner at Sequoia, Michael Manipat, CEO of road Space.

777
00:40:17,680 --> 00:40:19,600
Speaker 5: Joy having you both on, Thank you very much.

778
00:40:19,640 --> 00:40:23,239
Speaker 4: Indeed, coming up all eyes are on Jensen and in

779
00:40:23,360 --> 00:40:25,640
Speaker 4: Video and its earnings or on what a VESS can

780
00:40:25,680 --> 00:40:40,600
Speaker 4: expect visibly by attach. There are some big earnings to

781
00:40:40,680 --> 00:40:42,600
Speaker 4: keep on after the closing belt. And it's not just

782
00:40:42,680 --> 00:40:45,880
Speaker 4: in Vidia salesforce Snowflake. We've just been discussing with Brody

783
00:40:46,120 --> 00:40:48,120
Speaker 4: how the pressure is on these executives to fight the

784
00:40:48,120 --> 00:40:51,920
Speaker 4: good fight versus AI and disruption. We've got some both

785
00:40:51,960 --> 00:40:54,160
Speaker 4: trading higher ahead of the numbers. Zoom though off by

786
00:40:54,239 --> 00:40:57,319
Speaker 4: two percent. Again AI potential area of attack, but how

787
00:40:57,360 --> 00:40:58,320
Speaker 4: they continue.

788
00:40:57,960 --> 00:40:58,560
Speaker 5: To see growth.

789
00:40:58,560 --> 00:41:00,480
Speaker 4: We'll see we're off by two percent amount.

790
00:41:00,880 --> 00:41:02,120
Speaker 5: It's not all about M and A.

791
00:41:02,480 --> 00:41:04,799
Speaker 4: It's also about actual real growth that we're seeing in

792
00:41:04,800 --> 00:41:07,240
Speaker 4: the business and how they can afford to make fifteen

793
00:41:07,719 --> 00:41:09,680
Speaker 4: big movies a year. We'll see whether that slate can

794
00:41:09,719 --> 00:41:11,719
Speaker 4: be financed. But what do we think about in terms

795
00:41:11,719 --> 00:41:17,320
Speaker 4: of in video ed Because we are rallying into the numbers.

796
00:41:16,200 --> 00:41:18,400
Speaker 3: I think the bar is high and we are rallying

797
00:41:18,440 --> 00:41:20,560
Speaker 3: into the numbers. Let's get a preview with Bloomberzi and

798
00:41:20,640 --> 00:41:23,520
Speaker 3: King on Nvidia. Like you've covered this company for a

799
00:41:23,560 --> 00:41:27,040
Speaker 3: really long time. It does not typically miss earnings expectations,

800
00:41:28,320 --> 00:41:32,719
Speaker 3: but it's probably the best lever of AI sentiment you.

801
00:41:32,680 --> 00:41:33,120
Speaker 2: Can have.

802
00:41:34,800 --> 00:41:37,879
Speaker 3: What do you look for in a moment where beat

803
00:41:38,000 --> 00:41:40,880
Speaker 3: or miss isn't really what it's about. It's what mister

804
00:41:40,960 --> 00:41:43,799
Speaker 3: h Wong says on an own school that projects a

805
00:41:43,840 --> 00:41:44,640
Speaker 3: lot of oxtimism.

806
00:41:45,480 --> 00:41:47,400
Speaker 18: As you pointed out, I mean, in the last decade

807
00:41:47,440 --> 00:41:52,759
Speaker 18: it's missed earning revenue estimates twice so and sometimes it's

808
00:41:52,760 --> 00:41:55,600
Speaker 18: been by as much as twenty one percent. So you know,

809
00:41:56,239 --> 00:41:59,359
Speaker 18: good is a given for them, and that is what

810
00:41:59,400 --> 00:42:01,879
Speaker 18: the consens is is that you know the numbers will

811
00:42:01,920 --> 00:42:04,239
Speaker 18: be good. The concern is it'll be like last time

812
00:42:04,280 --> 00:42:08,359
Speaker 18: where Stellar isn't good enough, and you know the stock

813
00:42:08,360 --> 00:42:10,680
Speaker 18: will initially bounce and then maybe it goes down as

814
00:42:10,719 --> 00:42:14,279
Speaker 18: people start to say, yeah, we already know this exciters

815
00:42:14,320 --> 00:42:15,160
Speaker 18: give us something new.

816
00:42:16,080 --> 00:42:18,200
Speaker 5: Al it's really optimistic about the stock.

817
00:42:18,280 --> 00:42:20,920
Speaker 4: There's still only one cell rating remains the same as

818
00:42:20,960 --> 00:42:24,760
Speaker 4: always Seaport, so many eight buys and they do expect

819
00:42:24,840 --> 00:42:26,240
Speaker 4: shares to rally some two hundred.

820
00:42:26,000 --> 00:42:26,560
Speaker 5: And sixty three.

821
00:42:26,719 --> 00:42:28,480
Speaker 4: What do you think gets us there in in terms

822
00:42:28,520 --> 00:42:31,279
Speaker 4: of a catalyst, Because as we're hearing earlier, maybe we

823
00:42:31,440 --> 00:42:34,520
Speaker 4: see the big bold bets from Jensen held until GtC.

824
00:42:36,040 --> 00:42:40,200
Speaker 18: Yeah, a new product category. But even then, at this

825
00:42:40,320 --> 00:42:43,200
Speaker 18: point the numbers are so huge. We're talking, you know,

826
00:42:43,400 --> 00:42:47,240
Speaker 18: sixty percent year on year growth for a company that's

827
00:42:47,280 --> 00:42:51,919
Speaker 18: got tens of billions of dollars of revenue from one unit, right,

828
00:42:51,920 --> 00:42:54,160
Speaker 18: that unit happens to be bigger than pretty much any

829
00:42:54,160 --> 00:42:57,960
Speaker 18: other chip company. What do you do that can rival that?

830
00:42:58,040 --> 00:43:00,000
Speaker 18: What do you do that can make an impression on that?

831
00:43:00,040 --> 00:43:04,960
Speaker 18: So that's obviously difficult, really that the expectations keep feeding us,

832
00:43:05,040 --> 00:43:08,480
Speaker 18: keep feeding the beast, keep creating that belief that AI

833
00:43:08,680 --> 00:43:10,880
Speaker 18: is going to continue and is going to change the

834
00:43:10,880 --> 00:43:11,680
Speaker 18: world economy.

835
00:43:12,880 --> 00:43:15,520
Speaker 4: IIan King, It's going to be busy. Thanks so much

836
00:43:15,520 --> 00:43:17,400
Speaker 4: for joining us ahead of it. Meanwhile, that does it

837
00:43:17,480 --> 00:43:19,800
Speaker 4: for this important addition of Bloomberg Tech. We've got a

838
00:43:19,880 --> 00:43:21,960
Speaker 4: lot to look forward to later this day.

839
00:43:22,200 --> 00:43:22,279
Speaker 10: Ed.

840
00:43:23,080 --> 00:43:25,680
Speaker 3: Yeah, and like it is Nvidia everything, But as we

841
00:43:25,800 --> 00:43:29,040
Speaker 3: said throughout the hour, there are many other earnings directly related,

842
00:43:29,080 --> 00:43:32,200
Speaker 3: particularly Service now Snowflake in the software names.

843
00:43:32,000 --> 00:43:34,440
Speaker 5: That not service now, but yeah, certainly I'm.

844
00:43:34,280 --> 00:43:37,200
Speaker 2: Sorry so so fake salesforce exactly? All right? Check out

845
00:43:37,200 --> 00:43:37,480
Speaker 2: the pod.

846
00:43:37,520 --> 00:43:40,000
Speaker 3: You know where to find it on the Bloomberg platforms

847
00:43:40,239 --> 00:43:45,000
Speaker 3: and online on Spotify, Apple, and iHeart Brace, I guess,

848
00:43:45,120 --> 00:43:47,600
Speaker 3: and video is coming after market. This is Bloomberg Tech.