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Speaker 2: In joining us.
Speaker 3: And you know last night when this was blowing up,
Speaker 3: I said get me Mandeep saying.
Speaker 2: You'll join us in a bit here.
Speaker 3: But aniog Rana joins us now from Chicago with a
Speaker 3: little different take than Mandeep. More on the cloud, more
Speaker 3: on the systems analysis, if you will. Of these big companies,
Speaker 3: man Anerog, thank you so much for joining.
Speaker 2: You don't do biholed sell.
Speaker 3: But would you suggest the cell side will shift opinion today.
Speaker 4: For the cloud providers?
Speaker 5: I don't think so because, as you know Paul just
Speaker 5: mentioned about the tweet from my ACOFT CEO, he's probably
Speaker 5: a little bit happier because for him, if the cost
Speaker 5: curve goes down in the long run, and we don't
Speaker 5: know if that's going to happen, you know, his adoption
Speaker 5: rate goes up and his CAPEX goes down.
Speaker 4: So it's it's you know, in a roundabout way.
Speaker 5: Now, we don't think there is going to be an
Speaker 5: impact on CAPEX in the near term, but in the
Speaker 5: long run, if that just shifts, you know, it helps
Speaker 5: their profitability. But more important to that the enterprise you know,
Speaker 5: you could say take create on AI adoption goes up the.
Speaker 3: Theme this morning, Paul's been great about this is like
Speaker 3: drunken sailors from where in Anerich you're just world class
Speaker 3: at this. Are they drunken sailors in terms of CAPEX?
Speaker 3: Or is there a plan? Is there a sequence? Is
Speaker 3: there a pace to spending billions?
Speaker 5: So one of the things, if you would say, is
Speaker 5: if if this AI adoption curve, which is absolutely in
Speaker 5: infancy right now, the only thing we have seen is
Speaker 5: in the consumer world, if enterprises start to put this
Speaker 5: in their core app locations, then they would need a
Speaker 5: lot more you could say, firepower to run it. Most
Speaker 5: of the things that we have discussed is people would
Speaker 5: not want to do this on their own premise. They're
Speaker 5: bigger companies will but most of them will go to
Speaker 5: a handful of cloud providers, and that would be Microsoft, Aws,
Speaker 5: Google and then Oracle. So for all these companies to
Speaker 5: increase their capacity now they are only seeing the orders
Speaker 5: and based on that they are expanding their data center footwork.
Speaker 4: The question is whether do.
Speaker 5: They need the expensive chips to do with this or
Speaker 5: can they run this in with cheaper chips. And that's
Speaker 5: really I think the biggest discussion going to be over
Speaker 5: the next twelve months.
Speaker 6: An raglick Tom has often want to say, my head
Speaker 6: is spinning here. Just since Friday. I've got a big,
Speaker 6: big tech company called Meta I call it Facebook given
Speaker 6: the IPO. We spent a lot of time thinking about
Speaker 6: that name in the tech the ticker FB. They up
Speaker 6: their cap x from fifty billion to sixty five billion,
Speaker 6: a large part on AI. Now I've got this Deep
Speaker 6: Seek thinking about I can do this in.
Speaker 7: Much lower costs. How do we square those two things?
Speaker 5: Yeah, but one thing is for sure, this Deep Seek
Speaker 5: news of the paper has been out for a while,
Speaker 5: so it does got It did get publicized over the
Speaker 5: last few days. But I'd be very surprised if Meta
Speaker 5: AWS and Microsoft did not know about this. It has
Speaker 5: been around for a while, so both of them, both
Speaker 5: Meta and Microsoft talked about their capex last week after
Speaker 5: knowing this news, so you know they have moved.
Speaker 4: I mean, they're far smarter than I am when it
Speaker 4: comes to this.
Speaker 5: So if they're taking up their Capex, I mean there
Speaker 5: must be a real need for it.
Speaker 3: What's it mean for Coopertino there having an early morning?
Speaker 3: They don't have lotes at Coopertino? They got something, Lisa.
Speaker 3: What's the thing with the green powder in it?
Speaker 2: The machi?
Speaker 3: Yeah matter, they're having the machiat Coopertino some undrinkable bilge.
Speaker 3: What are they saying at Apple today?
Speaker 5: They're actually smiling and saying, you guys fight it out
Speaker 5: and tell me what's the best large language model out there.
Speaker 5: I'll just put it in my phone and I won't
Speaker 5: even pay for it. So they if you just look
Speaker 5: at you know, Apple right now, that's kind of the
Speaker 5: safety haven for people is they're not spending that capex.
Speaker 5: If you look at that Capex line, it hasn't moved
Speaker 5: at all in two years, and the free cash slow
Speaker 5: just keep on coming. Their issue, honestly, is more so
Speaker 5: on the you know, the growth side. They are having
Speaker 5: challenges in China that needs to you know, smoothened out
Speaker 5: over the next twelve months. Otherwise this is going to
Speaker 5: be another year for them. To grow only four five percent.
Speaker 5: That's the big issue for them. Nothing to do with AI.
Speaker 6: All right, Well, let's just stay on the Apple story.
Speaker 6: It stocks down eleven percent year to date this year,
Speaker 6: it's only a fifteen percent over the trailing twelve months,
Speaker 6: which is radical on the performance. And for a company
Speaker 6: like Apple, is there a bulkcase here short term?
Speaker 7: For Apple?
Speaker 5: In the short term, it's very difficult to come up
Speaker 5: with the bulkcase because, as we talked about it, even
Speaker 5: you know a few months ago, Apple Intelligence is not
Speaker 5: going to be out in other parts of the world.
Speaker 5: It's not out in China, and China is where they
Speaker 5: are struggling honestly at this and they need to come
Speaker 5: out and pacify investors that you know, we have a
Speaker 5: strategy in China, we will gain market share back. Otherwise
Speaker 5: this is going to be another mut the year for them.
Speaker 5: We think the next phone, which is the one that's
Speaker 5: coming out in September, I know that's fa I think
Speaker 5: that's the big catalyst, but that's like, you know, that's
Speaker 5: eight months out, nine months out.
Speaker 3: Right, and Agrana with us in Chicago right now. We
Speaker 3: welcome all of you on your commute across the Nation.
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Speaker 3: on radio right now. We adhere to their policy which
Speaker 3: is Ana Agarana and man Deep Sing can never be
Speaker 3: in the same ruct together. It's too much worse to
Speaker 3: the to the franchise. But Paul, why don't you bring
Speaker 3: in man Deep Sing?
Speaker 2: As we talked to both and Ruana and.
Speaker 6: Mandy man Deep Seeing covers the technology space along with
Speaker 6: Ana rog Rana, there are two leaders globally running our
Speaker 6: technology franchise and it is a global franchise analyst in Europe,
Speaker 6: Asia and North America. Man Deep, But I guess what
Speaker 6: we're hearing such Antela from Microsoft put out something that hey,
Speaker 6: cost coming down is pretty natural for the technology space.
Speaker 6: That happens, and it's a good thing because it helps adoption.
Speaker 8: Does that make sense to you, Well, clearly, I think
Speaker 8: the investor expectations were different, which is why you see
Speaker 8: this sort of stock reaction.
Speaker 7: So yes, we.
Speaker 8: Have Moore's law and we have other laws in terms
Speaker 8: of figuring out how the cost curve may look like
Speaker 8: over time. But clearly this is a step change in
Speaker 8: terms of, you know, what you can do with the
Speaker 8: existing chips that are out there, as well as what
Speaker 8: you will need going forward. So I think this is
Speaker 8: a big moment in terms of just that we can
Speaker 8: see with these chips and the kind of scale that
Speaker 8: is required for the next versions of these foundational models.
Speaker 8: But there is no doubt that this makes generative AI
Speaker 8: more accessible to software companies as well as you know,
Speaker 8: overall users.
Speaker 6: Anrak, what do you think this means to you know,
Speaker 6: I know you guys at Bloomberg Intelligence you have access
Speaker 6: to this I d C data, which is some of
Speaker 6: the best data on technology spending in the marketplace, and
Speaker 6: you guys feature that in your research. Is this going
Speaker 6: to change i DC's forecast of tech spending?
Speaker 7: AI spending? Do you think so?
Speaker 5: AI spending has been going up, Paul, We've talked about
Speaker 5: this a few times, but it's the other non AI
Speaker 5: spending that has actually not done so well in the
Speaker 5: last two years and over the next I would say month,
Speaker 5: month and a half, we will get a much clearer
Speaker 5: picture if corporations or enterprises are moving up there over
Speaker 5: our tech budgets or not, because right now AI spending
Speaker 5: is coming at the expense of areas you know, normal
Speaker 5: software or you know, just bording hardware upgrades or consulting
Speaker 5: that really needs to pick up because a large portion
Speaker 5: of the tech ecosystem is some of those companies.
Speaker 7: Mande.
Speaker 6: If I think when I think of this news today again,
Speaker 6: I'm like everybody else. Our listeners and viewers are learning
Speaker 6: about deep Seek and what it means. I can't help
Speaker 6: but think about TikTok at some point. Again, I feel
Speaker 6: like by the end of business today, we're gonna have
Speaker 6: a story coming into Washington. There's gonna be an opinion
Speaker 6: coming from Washington as it relates to deep Seek. Does
Speaker 6: oppose a similar risks? Do you think to TikTok from
Speaker 6: a regulator's perspective, Well.
Speaker 8: It's still the app is still you know, early in
Speaker 8: terms of adoption, and look, I'm sure it's got millions
Speaker 8: of users in East Asia and you know, China and whatnot.
Speaker 8: But I think when it comes to AI consumers, just
Speaker 8: look at the functionality, and you know the fact that
Speaker 8: they have an app wage is accessible for free as
Speaker 8: opposed to paying two hundred dollars a month, they'll end
Speaker 8: up using it. So it's the same argument with TikTok.
Speaker 8: You know they will go with the functionality. They don't
Speaker 8: care about the privacy and.
Speaker 3: The data man keep saying with us and ana ug Runa,
Speaker 3: we continue anerog, let's go to earnings. Let's like remove
Speaker 3: ourselves from deep seek. What is the character of the
Speaker 3: cloud mystery that you see in the earning season, Aniog.
Speaker 5: Yeah, we are anticipating in improvement in growth rates for
Speaker 5: both Microsoft and AWS going in. In fact, Microsoft, we
Speaker 5: are hoping they come out and increase their guidance for
Speaker 5: Azure numbers for the next two quarters. They have been
Speaker 5: struggling with supply challenges where they are not able to
Speaker 5: fulfill the demand that's coming in in their data centers,
Speaker 5: and if they give that signal that you know, that
Speaker 5: should revive or pacify some of the fears that we
Speaker 5: are seeing right now in the market. Same thing for
Speaker 5: a WS AWS has been talking about a recovery in
Speaker 5: consumption for their core business looking forward to some comments
Speaker 5: sometimes as well from them.
Speaker 4: So I'm hopeful that.
Speaker 5: Both companies will come up with good numbers over the
Speaker 5: next you know, ten days.
Speaker 3: But let's say it's not like you know, Procter and Gamble.
Speaker 3: It's not a unit and price store hit the revenue line.
Speaker 3: But where is the fear in the earning season analog
Speaker 3: on the income statement. Is it a margin fear, a
Speaker 3: revenue fear, or something I don't understand.
Speaker 5: I think it's going to be a backlock slash revenue
Speaker 5: fear more than the margins, because everybody understands this is
Speaker 5: a very you know, unique business. When you have a
Speaker 5: fixed cost business like this, you can scale it up
Speaker 5: in the near town, but once you reach a mature face,
Speaker 5: you know, all the revenue comes back, or you can
Speaker 5: distribute that over a very large platform.
Speaker 4: That has been the case for Cloud over the last
Speaker 4: you know, ten years.
Speaker 5: So in an expansion of capacity, people don't really you know,
Speaker 5: see that as a big issue in the near town
Speaker 5: man Deep.
Speaker 6: Last Friday, Meta took their capex guidance from fifty billion,
Speaker 6: which was consensus, which was kind of guidance, to sixty
Speaker 6: five billion. I've never seen that before. In order of magnitude,
Speaker 6: what's going on there.
Speaker 8: Well, and I guess they probably knew this deep Seek advancement,
Speaker 8: so it's not as if, you know, they were cut
Speaker 8: off guard with the deep Seek release, so they did
Speaker 8: it despite the you know, the whole thing around deep Seek.
Speaker 8: So to my mind, you know, every company is doubling
Speaker 8: down on AI right now, even though we are talking
Speaker 8: about pricing, compression and whatnot. But this is the moment
Speaker 8: where generative AI will be incorporated in all software, all applications,
Speaker 8: and every company wants a piece of it, so they
Speaker 8: don't mind spending more on County in.
Speaker 3: The room a ROD does a public one AI. Is
Speaker 3: there any interest that Lisa Mateo is waiting and waiting
Speaker 3: and waiting for AI.
Speaker 5: See, the thing is that the consumers have already embraced
Speaker 5: it through chat, GPT, through Gemini, through Perplexity. But when
Speaker 5: you look at the enterprise use case, we are still
Speaker 5: in the building phase. And that's probably this year is
Speaker 5: going to be like next year, we should see a
Speaker 5: much fostered adoption by companies in terms of and that
Speaker 5: you said will show up in cloud numbers right now.
Speaker 5: Even when you look for somebody like a Microsoft, most
Speaker 5: of their AI revenue is from consumer app, which is
Speaker 5: basically open AI is shock GPT.
Speaker 7: So all right, Tom, we like to talk to anog.
Speaker 2: Do you like Ludlow this morning?
Speaker 8: No?
Speaker 6: You just I mean we're likes will be Bloomberg Tech exactly.
Speaker 2: I mean, can you get the shoes with the White Souls?
Speaker 7: Yes, that's what David shoes.
Speaker 2: No, you weren't shoes of the White Souls.
Speaker 5: No, No, old school.
Speaker 6: And Tom, you know Man Deep and Hon they're pretty good.
Speaker 6: But the research, the real investment research on this whole
Speaker 6: Deep seek Chinese AI.
Speaker 7: Robert Lee. These are Bloomberg intelligence analysts in Hong Kong.
Speaker 6: So folks who have access to the Bloomberg terminal go
Speaker 6: there because Man Deep and they're just he was out
Speaker 6: with research a couple of months ago on this and
Speaker 6: he says, hey, this stuff is there.
Speaker 2: Okay.
Speaker 3: You know Lea in Uh in Hong Kong was way
Speaker 3: out front of this. Why are we stunned this morning?
Speaker 8: Well because he didn't found the table in terms of saying,
Speaker 8: my god, the table we're negative?
Speaker 3: Where are we negative? Three point five percent? In YAC
Speaker 3: right now? What I mean, let's bring it back to
Speaker 3: what happened. Why were we surprised.
Speaker 8: By this, No, I don't think you are surprised because
Speaker 8: open source has been talked about a lot. We have
Speaker 8: been talking about how companies are looking to you know,
Speaker 8: drive scaling uh at inference time, and how pricing was
Speaker 8: a constraint, and so look, this is the way the
Speaker 8: industry was headed. It's just that Deep Sea came out
Speaker 8: with a you know, a long paper that describes what
Speaker 8: they did in detail, and everyone else is kind of
Speaker 8: closed source. So being open source has its advantages, and
Speaker 8: that's what we're seeing with deep Seat here.
Speaker 6: So the baniers to entry here on ROD just in general,
Speaker 6: on AI are the banished entry low for AI.
Speaker 5: I think that's exactly what this paper that Mandep is
Speaker 5: alluding to is talking about. That you and I can
Speaker 5: go out and build some of this thing without much capital.
Speaker 5: Now the question is how are you going to distribute it?
Speaker 5: And which is why I go back to the cloud
Speaker 5: providers that those are the guys who are going to
Speaker 5: work with enterprises to embed some of this technology. If
Speaker 5: you look at somebody like an AWS, they work with
Speaker 5: all these providers, they work with Meta Islama model or
Speaker 5: Anthropics cloud models. So it's really up to the customer
Speaker 5: which model they choose or sometimes they would write the
Speaker 5: reroute the inquiry based on what's better for that particular question.
Speaker 4: So it's really the distribution.
Speaker 5: What I'm saying is is the value here which takes
Speaker 5: us back to the cloud providers and also do Apple.
Speaker 3: This has been fun erragran and your trooper to get
Speaker 3: up this early in Chicago aner Agroana with Bloomberg Intelligence
Speaker 3: at Man Deep saying, can we say on behalf of
Speaker 3: all of us?
Speaker 2: Mandep, thank you much.
Speaker 3: Okay, we'll try not to do it three times tomorrow,
Speaker 3: maybe once, or maybe we'll see.
Speaker 2: A Wednesday or whatever.
Speaker 3: Man Deep sing and enter Agrana. Is what the show
Speaker 3: is about, just world class on tech analogy.
Speaker 1: You're listening to the Bloomberg Surveillance Podcast. Catch us live
Speaker 1: weekday afternoons from seven to ten am Eastern Listen on
Speaker 1: Applecarplay and Android Otto with the Bloomberg Business app, or
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Speaker 2: We Get Lucky.
Speaker 3: Joe Wisenthal has done so much for Bloomberg, I should say,
Speaker 3: for business journalism, and of course it's work here at
Speaker 3: Bloomberg with Tracy Alloway. But one of the great things
Speaker 3: is he did Paul, he you know, I'm like a
Speaker 3: I E I E I O. Joe's actually doing it,
Speaker 3: he said, no, but but nobody. He looked at the
Speaker 3: summer tour of Light Sweet Crude and said, I can't
Speaker 3: do the Light Sweet Crude analysis without AI. You three
Speaker 3: days ago you nailed deep Seek. You're using it at home. Yeah,
Speaker 3: what's the experience of deep Sea?
Speaker 9: So I'll just see the main There are two main
Speaker 9: takeaways for me. One is I have never experienced any
Speaker 9: technology in the history of any tech, computers, apps, whatever,
Speaker 9: that have zero switching.
Speaker 7: Costs the way AI chatbots have.
Speaker 9: I used Chad GBT for a long time. Claude came out,
Speaker 9: the one from Anthropic, I was like, oh, this works Gemini.
Speaker 9: I used Gemini now that for some reason, that one
Speaker 9: hasn't sucking as much then I. But then deep Sea
Speaker 9: came out and I said, or I saw the chap
Speaker 9: out last week online and I was like, I'm gonna
Speaker 9: try this out. It took me thirty seconds to register,
Speaker 9: and I was like, this is just as good as
Speaker 9: what I'm getting from Chad. You know, I ask at
Speaker 9: random things during the day and.
Speaker 2: It's just zerop radio. It's all, you know.
Speaker 9: I asked a random historical questions or linguistic I'm interested
Speaker 9: in Lenco, like.
Speaker 2: Why did Texas lose to Ohio? No, I can't. That's
Speaker 2: too painful. I don't ask that.
Speaker 9: But then the other thing is I made a twenty
Speaker 9: twenty five one of my New Year's resolutions. Yep, I've
Speaker 9: never I said I'm going to try and code something
Speaker 9: with AI one of my goals. Yeah, And so I
Speaker 9: started like building a little software. But I just asking
Speaker 9: to create this code, and uh, I was able to
Speaker 9: plug my app that I'm building on my home. It's
Speaker 9: a little linguistics app into the Deepseek API, and it's
Speaker 9: like a fraction of the cost of what I use
Speaker 9: for the open AI API. So, like I just played
Speaker 9: around with it. I was like, Wow, here's this thing
Speaker 9: that seems just as good as changchipyt. Sorry, here's this thing.
Speaker 2: That seems just good changing formosa.
Speaker 6: So yes, I'm not surprised that, Like, all right, the
Speaker 6: dumb question there, Yeah, are we not using Google anymore
Speaker 6: because of this?
Speaker 10: No?
Speaker 9: I still well, look it is you know, like I
Speaker 9: still do. I still use Google all the time. I
Speaker 9: still use Wikipedia all the time. They're just different.
Speaker 7: But what's your initial go to, oh, I need to
Speaker 7: know about this.
Speaker 9: I think it really depends on the context. I say,
Speaker 9: I really like using AI for things like understanding a
Speaker 9: term within a specific context or something like that or something.
Speaker 9: But you know, like you don't know if it's true,
Speaker 9: So you know, I always do a backup. I see
Speaker 9: something and then I say, oh, look at Google is
Speaker 9: like is this actually true?
Speaker 3: Morgan Brown, Dropbox Imperial w He's out with the smartest
Speaker 3: note I've seen where he's talking about decimal points. I
Speaker 3: don't want to go into that. You and Tracy at
Speaker 3: audience talk a lot more to techy people about this.
Speaker 3: What's their message on the future of American AI versus
Speaker 3: these shock threats.
Speaker 9: I mean, you know what, here's what my my take,
Speaker 9: which is that they're already I mean, we saw the
Speaker 9: Trump announcement last week with Stargate right half a trillion dollar.
Speaker 3: I thought that was I thought that was the movie
Speaker 3: with what's happening now?
Speaker 9: I think because of the arrival of this very compelling
Speaker 9: Chinese model, is it just cements the notion that there
Speaker 9: is a global arms race allah the bomb And I
Speaker 9: don't know if achieving AGI or whatever people talk about
Speaker 9: is a breakthrough on par or is strategic as a
Speaker 9: nuclear bomb. But now everyone is just going to be
Speaker 9: we have to beat them, we have to beat them,
Speaker 9: and there's gonna be so much money flowing to tech
Speaker 9: companies now in this idea that there is a global race, Joe.
Speaker 6: I feel like by the end of business today, the
Speaker 6: top star on the Bloomberg terournal will be US government
Speaker 6: looking at deep Seek as it's looking at TikTok TikTok.
Speaker 7: Well, you know what, so this is interesting.
Speaker 9: The other thing, and thanks for reminding me of this,
Speaker 9: which is that deep Seek is a piece of open,
Speaker 9: open source software. It is it's unbannable. Now, there is
Speaker 9: an app that theoretically could be banned from the app store,
Speaker 9: but I think it'll be high. But it's a piece
Speaker 9: of open source software.
Speaker 3: I have a friend.
Speaker 9: You know, you can run it on your own computer
Speaker 9: if you have the And so this is fundamentally different
Speaker 9: from TikTok in the sense that anyone can run this
Speaker 9: piece of code, just download it, and so it's fundamentally unbannable.
Speaker 3: You've been on fire, Adam Tooms this weekend. Very nice,
Speaker 3: come your euro dollar three part series. You have Howard
Speaker 3: Marx on Good morning, mister Mark, thank you so much
Speaker 3: for your support over the years. What's your message from
Speaker 3: Howard Marx about this?
Speaker 9: Odd He doesn't think we're in an AYE bubble yet,
Speaker 9: he said, you know, he like doesn't zuberans he doesn't see,
Speaker 9: which I thought was really interesting because to me, it
Speaker 9: feels like exuberance. But the idea of me questioning Howard
Speaker 9: marks on questions like what is exuberance really feels like
Speaker 9: someone who has experienced multiple cycles over the years, right,
Speaker 9: I don't think I would go with my take versus take.
Speaker 2: Okay, did you go to NAM were you out?
Speaker 4: And well?
Speaker 3: Well, I mean the endorsements like sweet crudez. Should I
Speaker 3: go with the Gratch, pink Rander Penguin?
Speaker 2: I mean, that's what's got the fishman pick you got it?
Speaker 2: You got it? I mean it's five forty nine and Sweetwater.
Speaker 2: I'll tell missus that's like you got to it's free
Speaker 2: and it's pink.
Speaker 7: Is that done with the Jeff?
Speaker 4: Oh?
Speaker 3: Yeah, they did, Joe bid But I'm sorry, Wretches on fire,
Speaker 3: Retches on fire, that's the real break. Fender bought Gretch
Speaker 3: and you know what's light sweet crew?
Speaker 2: Doing you playing.
Speaker 9: We have a show this Wednesday the eleventh Street Bar
Speaker 9: in Manhattan. It's free, eight o'clock East Village. Everyone should
Speaker 9: come out. We're gonna play some new songs.
Speaker 2: Are you really for?
Speaker 3: And I like, you know, I'm in bed at a thirty?
Speaker 3: Does it really start at eight? Or are you doing
Speaker 3: the rock star?
Speaker 9: Do we have an opening act at eight? We're going
Speaker 9: to be on just after nine? But you know after
Speaker 9: come out one night. It's one night, yeah.
Speaker 7: But the next morning have one.
Speaker 9: You have one off day the next day.
Speaker 2: Okay. So you got Howard Marks coming up online out today.
Speaker 2: Check it out?
Speaker 3: Okay, Joe Wisenthal, thank you so much and really folks
Speaker 3: followed Joe the Stalwart and uh on Twitter, and also
Speaker 3: followed Joe on LinkedIn where he's really going step by
Speaker 3: step through his experience with AI, which I think is
Speaker 3: really cool.
Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday
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Speaker 3: Stacey Raskin is double chemical engineering definitive out of UCLA
Speaker 3: and mit he wandered back to the Avenue of the
Speaker 3: Stars where he is a star for Bernstein. What you
Speaker 3: need to know is in the old days, you had
Speaker 3: a black covered book from Sanford Bernstein and you knew
Speaker 3: good morning Brad Hints that you were dealing with the
Speaker 3: best Stacy honored that you could join us this morning.
Speaker 3: Will you change by hold sell on the American tech
Speaker 3: companies because of this Deep Seak announcement, I mean.
Speaker 2: Lok, so we're not change.
Speaker 10: We haven't changed anything. We get killed ourselves over the
Speaker 10: weekend to go through some of this stuff and put
Speaker 10: some views in places like I had three kind of
Speaker 10: broad takeaways please from yeah, from from from the work.
Speaker 10: But number one is I think there's been a headline.
Speaker 10: But I think this is why the circus. There was
Speaker 10: a headline that kind of came out all is that
Speaker 10: was kind of like, hey, deep Sea duplicated open AI
Speaker 10: for five million dollars, and then went so I do
Speaker 10: not think they duplicated open AI for five million dollars.
Speaker 10: Number two, Look, I think the models that they built
Speaker 10: are fantastic. They're really really good. But I don't think
Speaker 10: they're miracles. We can talk about why and and number
Speaker 10: three finally, like, I think the panic and there's clearly
Speaker 10: a full blown on panic going on over the weekend
Speaker 10: and this morning, I think it's overblown. I think, you know,
Speaker 10: I do not think that deep seek is the doomsday
Speaker 10: for for AI infrastructure.
Speaker 2: For those of you are for those of you are
Speaker 2: on radio.
Speaker 3: On YouTube, you can see a space shuttle behind a
Speaker 3: gentleman from m I T I.
Speaker 10: I didn't even know that I lived.
Speaker 3: That Stacey, and we were certain it worked until the
Speaker 3: heat panels didn't work in January of nineteen eighty six.
Speaker 3: Do we have a certitude that the stuff is going
Speaker 3: to work for Nvidia or Microsoft? Are the other fourteen
Speaker 3: names you follow?
Speaker 10: I cover ten names Microsoft and some of the others
Speaker 10: are covered by my college cover semicaracters. When you talk
Speaker 10: about work, like, I don't understand what you mean. But
Speaker 10: the question here is these models look really efficient, and
Speaker 10: the resources that were required to train them, you know,
Speaker 10: look lower than what we've seen from some other models
Speaker 10: in the past. And then even you look at where
Speaker 10: they're actually pricing the stuff, and they're pricing and they're
Speaker 10: pricing it at levels that are quite a bit lower
Speaker 10: where say open ay makes their models available on if
Speaker 10: you want to go use them. And so the question is,
Speaker 10: given all of that that you need less, you need
Speaker 10: fewer GPUs, that's that's the big one, and fewer infrastructure
Speaker 10: buildouts and everything else. And so I mean, just just
Speaker 10: to talk about it's like, what have they done. They've
Speaker 10: got two flavors of models. They've got something called V three,
Speaker 10: which is sort of like a chat model. It uses
Speaker 10: something called a mixture of experts that makes it very efficient.
Speaker 10: And they've got a reasoning model called one where they
Speaker 10: used reinforcement learning and some other techniques from the V
Speaker 10: three base model to build rivals to say to open
Speaker 10: a eyes one reasoning model. If you look at the
Speaker 10: why they're so efficient in terms of the training that
Speaker 10: they did on and the compute resources they used to
Speaker 10: train the V three models, it's very efficient. They compared
Speaker 10: it to say like LAMA four or five B, and
Speaker 10: it took you know, roughly ten percent of the computer
Speaker 10: resource to train it then metas a LAMA four or
Speaker 10: five B did. However, the structure of the model, would
Speaker 10: that make sense? It uses something called a mixture of experts.
Speaker 10: That's the whole point. Other mixture of experts, models that
Speaker 10: are out there, you know, take anywhere from you know,
Speaker 10: a six to one seventh as mount compute resources.
Speaker 2: This is a good one.
Speaker 10: It was like one tent or even even better than that.
Speaker 10: But I don't think it's a miracle. And you got
Speaker 10: to remember, like remember I'm a semiconductor analyst. Like for
Speaker 10: fifty years, costs and semiconductors got cut in half, like
Speaker 10: for every every cheers for fifty years. That was not
Speaker 10: a bad thing for semiconductor man, that was a good thing.
Speaker 10: We all want adoption. To get adoption, we need lower costs.
Speaker 10: This is something called Jevans paradox, right, like increasing efficiency
Speaker 10: drives actually more demand, more net demand, not less demand.
Speaker 10: I'm a firm believer in that. I have a strong
Speaker 10: suspicion that if we can free up more compute resources,
Speaker 10: it will get it.
Speaker 2: Will be used.
Speaker 10: I don't think we're anywhere close to the end of
Speaker 10: compute needs for artificial intelligence. We're gonna need this just
Speaker 10: given I mean.
Speaker 2: The costs have been going up. Right next year, we
Speaker 2: need this.
Speaker 3: But anytime anybody coast William Stanley, Jefvins on the show,
Speaker 3: they get to come back.
Speaker 7: They get to continue.
Speaker 6: Stacey, what do you expect to hear from the semiconductor
Speaker 6: companies that you cover in terms of their response to
Speaker 6: this news, whether it's and video or others.
Speaker 10: Yeah, well, I mean, so we were in the middle
Speaker 10: of earning season right now, so we'll see as they
Speaker 10: come out, right, but we forget the semiconductor comings from it.
Speaker 10: We've already seen, like like some of the other like responses,
Speaker 10: and you have to remember everything that that that we've
Speaker 10: seen deep seaking like this. I don't want to I
Speaker 10: don't want to dismiss it like they're they're really good
Speaker 10: and very efficient, they're very smart engineers. But this is
Speaker 10: these are not things that are not known, and you know,
Speaker 10: these are not things that like the the other top
Speaker 10: tier AI researchers and AI labs are not aware of
Speaker 10: and potentially already using themselves. Right, And if we look
Speaker 10: at what we saw last week on top of all
Speaker 10: of this, clearly spending is going up, not down. So
Speaker 10: Meta just just significantly increased their capex. I think on Friday,
Speaker 10: right we had the whole Stargate announce and five hundred
Speaker 10: billion dollars whatever that is, and even China a few
Speaker 10: days ago announced a one trillion yuan which is about
Speaker 10: one hundred and forty billion dollar US sort of like
Speaker 10: sovereign like AI effort right, so like clearly spending is
Speaker 10: still going up, not down. And and these models, I said,
Speaker 10: they didn't just just dump on us. Yesterday, the Deep
Speaker 10: Seat V three was released the end after just.
Speaker 3: Well, Tracey Stacey, I got to get this in. It's
Speaker 3: too important. At UCLA. You had to survive Physics one
Speaker 3: A a few years ago. The smartest thing I've seen
Speaker 3: is that American AI is trying to go out to
Speaker 3: thirty two decimal points, where the Chinese are saying, you
Speaker 3: know what eight decimal points is?
Speaker 2: Okay?
Speaker 3: Is this a question of granularity or we're being too
Speaker 3: perfect in AI? And the Chinese are saying, you don't
Speaker 3: need to be too perfect.
Speaker 10: Now, so they use what you're trying. They use mixed precision.
Speaker 10: They use mixed precision numbers to train this that they
Speaker 10: used to have floating point eight eight bit numbers you
Speaker 10: typically use floating point sixty or floating point thirty two.
Speaker 10: It's actually really interesting though, in Vidia with their Hopper generation,
Speaker 10: which is the H one D eight hundreds. It has
Speaker 10: something called on it. It's actually called a transformer engine.
Speaker 10: What that actually did was it enabled you to train
Speaker 10: at eight bit precision. And in fact Blackwell, which is
Speaker 10: their their their next generation stuff, this spending on now
Speaker 10: actually enables four bit precision. So no, these are things
Speaker 10: that everybody is looking at. It may it may be
Speaker 10: that that deep Seek is the first ones to actually
Speaker 10: deploy this in a very large model, but these are.
Speaker 2: Things they're looking at it.
Speaker 10: And if you actually look over time, we've seen the
Speaker 10: numerical precisions that people are using coming in and other
Speaker 10: the reason you do this, did you get more compute?
Speaker 10: If I go from sixteen bit to eight in theory,
Speaker 10: I get twice as many flops, twice as many operations
Speaker 10: per second. But no, these are things that have been
Speaker 10: happening all along. This is just the next step. And
Speaker 10: they're again I don't want to dismiss them, Like I said,
Speaker 10: they've done some really clever things and but but none
Speaker 10: of this is a miracle or and none of this
Speaker 10: I think is an unknown or a slap in the
Speaker 10: face to the other AI labs.
Speaker 3: We're out of time. Don't be a stranger thing. You're
Speaker 3: trooper to get up this early. Really really appreciate these.
Speaker 3: In Los Angeles daily lunches at Michael's. They're closed now
Speaker 3: because of the fire, but I'm sure when Michael's reopened,
Speaker 3: you know Stacy will be there. Stacy redskin with burns,
Speaker 3: definitive there.
Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday
Speaker 1: starting at seven am Eastern on Applecarplay and Android Auto
Speaker 1: with the Bloomberg Business app. You can also watch us
Speaker 1: live every weekday on YouTube and always on the Bloomberg terminal.
Speaker 3: The daily look at the front pages. It's brought to
Speaker 3: you by IBKR. With the average US temperature in January
Speaker 3: twenty twenty five be greater than thirty four degrees. Trade
Speaker 3: your prediction with IBKR forecast Trader that yes was recently
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Speaker 2: We dashed to the newspapers. Lisa tell me we're deep,
Speaker 2: deep seek free.
Speaker 7: We are newspaper free.
Speaker 11: I know, trying to do something a little different. We
Speaker 11: talked about more companies pushing workers back to the office, right,
Speaker 11: but not everyone at the company is being treated the same.
Speaker 11: They're saying. It's causing a lot of tension now in
Speaker 11: the workplace because you have some people in a company,
Speaker 11: like the top performers, the employees with those certain skill sets.
Speaker 11: They're being given that flexibility, and so he comes in
Speaker 11: once in a while because the companies don't want to
Speaker 11: lose them to other companies. You know, it's a whole
Speaker 11: thing of stealing each other's workers. So it's a lot
Speaker 11: of tension in the workplace that's starting to cause attention
Speaker 11: between the managers and the staff on top of it.
Speaker 3: So it's truly fluid, I mean into the warmer season
Speaker 3: into spring.
Speaker 2: To me, it's a hugely fluid debate.
Speaker 7: Some people take Fridays off in the summertime.
Speaker 2: I've heard, well they do.
Speaker 7: Yes, I've heard we missed that memo.
Speaker 2: It works.
Speaker 3: It works out with me in PA because he takes
Speaker 3: every Friday off, and I'm like, you know, you're in
Speaker 3: the fam and all that.
Speaker 7: It works out.
Speaker 11: Nextll does we want to go to the airline industry
Speaker 11: because you're seeing this shift in the pricing power now
Speaker 11: going back to the carriers. If you've been pricing tickets
Speaker 11: out there, notice prices for the cheapest flights up twelve
Speaker 11: percent this month from a year earlier. That's according to Hopper.
Speaker 11: But the airlines are saying people are gonna pay it
Speaker 11: no matter what. And they're saying people are paying it domestic, yes,
Speaker 11: international as well.
Speaker 8: And there.
Speaker 11: I don't know, I don't know how much of a
Speaker 11: deal there you got, But they're saying what's shifting to
Speaker 11: is that the discount airlines. You know, you've seen them
Speaker 11: who usually go to these you know consumer you know,
Speaker 11: budget conscious people. They are starting to shift to the
Speaker 11: to the more advanced. And then you have the luxury sector.
Speaker 11: Now you have all these luxury items being offered out
Speaker 11: on the plane. So if you go on a flight,
Speaker 11: you may have a you know, a cosmetic bag filled
Speaker 11: with all these premium you know, lotions and perfumes. You're
Speaker 11: getting caviars, champagne, cae.
Speaker 4: You have not seen.
Speaker 11: You haven't gotten your crystal champagne.
Speaker 2: What is it Hudson River, Yeah, exactly right.
Speaker 6: I mean it's everything's a cart though you pay for
Speaker 6: everything now, so I mean, you know the bags that
Speaker 6: that that the better seats so.
Speaker 3: We had an offspring at the airport with a lot
Speaker 3: of luggage. Call up and say, I can't believe what
Speaker 3: they're you know, yep, they want it for me right now,
Speaker 3: for three extra bags or.
Speaker 7: Whatever, two weeks in Europe with one check on check it. Yep,
Speaker 7: I don't take it. You don't take a bag. I
Speaker 7: don't take the kids.
Speaker 2: They travels, they take too much stuff today.
Speaker 11: Next, lastly, okay, so you heard about costco is switching
Speaker 11: back from coke back to coke from pepps. Really, yeah,
Speaker 11: that's that's huge for you. I know, Paul, you know
Speaker 11: you're the Coke.
Speaker 6: Pepsi coke person. But I won't die on that hill.
Speaker 6: You will put PEPs in front of me.
Speaker 7: I'll be fine.
Speaker 11: But it's like this huge debate on.
Speaker 3: Someone to explain a Costco on a Saturday morning Cocono Pepsi.
Speaker 4: Yeah.
Speaker 11: People are like Ritt. They want it with their dollar
Speaker 11: fifty hot dog. They want to have their certain soda
Speaker 11: because they're used to it.
Speaker 2: Can you tell the difference?
Speaker 7: I can't wait.
Speaker 2: Wait, you haven't had mix?
Speaker 3: Now.
Speaker 6: I'm the soda person here and I actually have almost
Speaker 6: a year and a half. I put in a ticket
Speaker 6: every day to bring back the soda machines on the
Speaker 6: sixth floor. It's going up to the highest level of
Speaker 6: bloom But if you.
Speaker 11: Did the blind taste test, could you tell you yes,
Speaker 11: you could?
Speaker 4: You can.
Speaker 2: Yeah.
Speaker 6: But again, I'm a coke person, but you put a
Speaker 6: PEPs in front of me just as happy.
Speaker 7: I mean, I don't know anybody else back there coke
Speaker 7: PEPSI I don't know who cares. I don't know.
Speaker 6: But the organic stuff they have on the sixth floor
Speaker 6: has to go. If somebody's listening that can do something
Speaker 6: here at bloom or get rids.
Speaker 7: They have organic soda on the sixth floor. I mean,
Speaker 7: that's un American. It's un America exactly.
Speaker 6: So I'm talking to the highest people in here at
Speaker 6: Bloomberg to get our soda.
Speaker 2: Machines, the newspapers. Lisa Mateo, thank you so much.
Speaker 1: This is the Bloomberg Surveillance podcast, available on Apple, Spotify,
Speaker 1: and anywhere else you get your podcasts. Listen live each
Speaker 1: weekday seven to ten am Easter and on Bloomberg dot com,
Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app.
Speaker 1: You can also watch us live every weekday on YouTube
Speaker 1: and always on the Bloomberg terminal