Speaker 1: Bloomberg Audio Studios, Podcasts, radio news.
Speaker 2: This is Bloomberg business Week Insight from the reporters and
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Speaker 2: global business, finance and tech news. The Bloomberg Business Week
Speaker 2: Podcast with Carol Masser and Tim Stenoveek on Bloomberg Radio.
Speaker 3: Our first guest, he's part of the family, Man Deep Sing.
Speaker 3: He doesn't know, but we're not going to let him
Speaker 3: go for sixty minutes because there's so much to talk about.
Speaker 3: When it comes to Deep Seek, we want to get
Speaker 3: into it. As you know, it's the Chinese artificial intelligence
Speaker 3: startup Deep Seek, their latest model AI model, sparking a
Speaker 3: one trillion dollar route in US and European technology stocks.
Speaker 3: We have been seeing this AI shot play around the
Speaker 3: globe on this Monday. A lot of questions though about
Speaker 3: maybe valuations here in the United States, but what it
Speaker 3: really means in the AI race. So let's get to it.
Speaker 3: Man Deep is Bloomberg Intelligence Senior Tech industry unless Man
Speaker 3: Deep seeing he's here in studio. You've been up early.
Speaker 3: We've been listening to you, both Tim and I throughout
Speaker 3: the day. Why is this all happening? Because for your world.
Speaker 3: You guys, this has been on your radar, But why
Speaker 3: is it all of a sudden on our radar and
Speaker 3: why should we care or shouldn't we care?
Speaker 4: Well, every company has been talking about how capex needs
Speaker 4: to go up because they believe in scaling laws. I
Speaker 4: think what this development has shown is the hardware that
Speaker 4: these companies have procured, they weren't using it efficiently and
Speaker 4: literally it's both on the training side as well as
Speaker 4: the inferencing of the models when it comes to using
Speaker 4: it in chatbots and so on. And that's where I
Speaker 4: think you have to ask yourself as an investor, are
Speaker 4: you ready to pay up for these companies when they are,
Speaker 4: you know, increasing their capex when we know they're not
Speaker 4: running it efficiently. So I think a lot of questions
Speaker 4: around just the efficiency of the hardware. I mean, the
Speaker 4: scaling will continue just because there is more demand to
Speaker 4: incorporate AI, but the fact that you know this model
Speaker 4: does it so much more efficiently, I think raised a
Speaker 4: lot of questions.
Speaker 5: Does it show that deep Sinck is actually ahead of
Speaker 5: open AI, of Anthropic, of Lama at Facebook?
Speaker 4: No, In fact, they are using the output of open
Speaker 4: AI and Anthropic and Lama to train their own models.
Speaker 4: So think about this, Deep Sea. Didn't you know, train
Speaker 4: this model from scratch the way open ai did. They
Speaker 4: used output from open AI's models to train its own model.
Speaker 4: So in effect, they are paying open ai, you know,
Speaker 4: for all the API calls. But then they didn't have
Speaker 4: to do things from scratch. And that's where you know,
Speaker 4: if you are a meta Llama who has invested billions
Speaker 4: of dollars in creating LAMA model, what was their incentive
Speaker 4: to open source it to begin with? Because open sourcing
Speaker 4: it made it easy for someone like deep Seek to
Speaker 4: build their own model. And that's the thing about open sources,
Speaker 4: you lose your IP. Someone else can come up with
Speaker 4: a better approach to do things more efficiently, and suddenly
Speaker 4: everyone runs to them.
Speaker 3: Man, Deep is this like the Apple Store. You don't
Speaker 3: have to be first, you just have to be better.
Speaker 3: Like I'm thinking about like creating a smartphone.
Speaker 4: I won't compare them to Apple yet, I mean, they'll
Speaker 4: have their problem when it comes to distributing this model.
Speaker 4: There's no way I can see, you know, Deep Seek
Speaker 4: getting to the adoption of open Ai, especially here in
Speaker 4: the US. But at the same time, you have to
Speaker 4: give them credit for you know, just being novel in
Speaker 4: terms of you know, the limited GPUs they had and
Speaker 4: how they ended up using them.
Speaker 3: Do you trust the information, the research, and do you
Speaker 3: trust that what they say they did they did do?
Speaker 4: Probably not. If they are saying six million dollars for
Speaker 4: training their entire model, I don't trust it because when
Speaker 4: I look at OpenAI costs for training their you know,
Speaker 4: GPT four model, it was close to three hundred million.
Speaker 6: So we are talking about a fifty x gap.
Speaker 4: Now, even if Opening Eye wasn't very efficient, I don't
Speaker 4: buy the fifty x gap. So clearly, you know there
Speaker 4: is something that they are not counting when they you know,
Speaker 4: release the paper. But at the same time, they've give
Speaker 4: given us enough evidence to show that they are doing
Speaker 4: things much more efficiently on the hardware side because of
Speaker 4: the constraints they had Men Deep.
Speaker 5: I know you don't cover in video, and we're gonna
Speaker 5: be speaking to Ian King in just a few minutes,
Speaker 5: who's been covering in video in the ship space for years.
Speaker 5: But we can't ignore that in videos down close to
Speaker 5: eighteen percent right now. I mean it's shed almost a
Speaker 5: fifth of its value in just today. Yes, the run
Speaker 5: up over the last couple of years has been immense,
Speaker 5: but a day like today is just mind boggling. I
Speaker 5: think for a lot of people should in video in
Speaker 5: your view be worried.
Speaker 4: I mean, look, that's where a lot of the questions
Speaker 4: come is the cost for training the next model. So
Speaker 4: if deepseek is saying that the cost was six million,
Speaker 4: I think it should be really worried. But a lot
Speaker 4: of people are apprehensive of that six million number because
Speaker 4: they think it'll be higher. And it won't be three
Speaker 4: hundred million the way open Aies was, but it will
Speaker 4: be higher. And that's where I think open Ai or
Speaker 4: Entropic will have a very tough time selling to their
Speaker 4: investors that they need to build a one million GPU
Speaker 4: cluster to train the next version of their model.
Speaker 7: Mandi, does this show that even though the US has been.
Speaker 3: Pretty rough in terms of restricting advanced technology, going over
Speaker 3: to China, does this show that Chinese R and D
Speaker 3: and Chinese companies can be pretty scrappy and pretty smart
Speaker 3: and maybe figuring a go around and coming up with
Speaker 3: their own way of competing against Nvidia.
Speaker 8: And the like.
Speaker 4: Yeah, and look, I think this could be another way
Speaker 4: of them saying Look, we are open sourcing whatever we
Speaker 4: have learned so far. So they want to build a
Speaker 4: community because the export restrictions aren't going away, so they
Speaker 4: are not going to get the you know, black ball
Speaker 4: chips on paper and all the other allocation. And the
Speaker 4: thing about model training is it's continuous. It's not a
Speaker 4: one and done thing. So you have to continuously improve
Speaker 4: your model. The other labs will go ahead if they
Speaker 4: are not able to, you know, keep doing the training
Speaker 4: and all the other stuff that other labs are doing.
Speaker 4: So from that perspective, I think the whole aspect of
Speaker 4: community building is front and center here. Yeah, but I
Speaker 4: still think the cost parity is a very big concept here.
Speaker 5: Hey, before we let you go, Mandy, you do cover
Speaker 5: meta platforms. The company out on Friday, Mark Zuckerberg saying
Speaker 5: he was going to be spending more on Capex than
Speaker 5: previously announced. Then the stock moved higher on Friday. Stock
Speaker 5: was lower earlier in the session, but higher now. I mean,
Speaker 5: I look at a move like that today and that
Speaker 5: runs counterintuitive to kind of everything we're talking about.
Speaker 4: Look, there is a lot of confusion, but if there's
Speaker 4: one thing that happened today is this moment is good
Speaker 4: for open source, and meta Lama is an open source model,
Speaker 4: so if anything into open source does get a nod
Speaker 4: when it comes to you know what deep seek is
Speaker 4: touting here.
Speaker 3: But you do also think about if it's cheaper for
Speaker 3: companies to build out, then does everybody have to rely
Speaker 3: on some of the bigger players.
Speaker 7: Maybe not.
Speaker 4: Next time Meta Lama will collect a fee from deep
Speaker 4: seek for you know, using their model to train their
Speaker 4: own models, so that could be a positive.
Speaker 3: I love this world that keeps us on our toes men,
Speaker 3: deep saying keeps us on the straight and narrow. He's
Speaker 3: Bloomberg Intelligence senior tech industry analyst here and has been
Speaker 3: all over this story. We want to focus a little
Speaker 3: bit more on semiconductors because we have seen that group
Speaker 3: really taking a beating. You've got almost all thirty names
Speaker 3: twenty eight out of thirty down in the Philadelphia Semiconductor
Speaker 3: Index down about ten percent, the index as a whole.
Speaker 3: Nvidios down seventeen percent. So ouch, what does this mean
Speaker 3: for Nvidia specifically? We get to now Bloomberg News US
Speaker 3: semiconductor and networking reporter Ian King. He's out there in
Speaker 3: San Francisco. I don't know Ian, how we've all been
Speaker 3: like talking about this non stop today you're the expert.
Speaker 3: How are you thinking about Nvidia and possible impact the
Speaker 3: reality of it all?
Speaker 7: How do you see it?
Speaker 9: I mean a lot depends upon how much reality there
Speaker 9: actually is behind this claim behind you know, it was
Speaker 9: a very well set out, well referenced research paper at
Speaker 9: this point, and the model has been open sourced and
Speaker 9: we'll see what people can do with it. The implication is,
Speaker 9: of course that things got cheaper, things got more simple,
Speaker 9: but we'll have to see that manifest itself in the
Speaker 9: real world. And then obviously you can absolutely bet that
Speaker 9: in video and a lot of other computer scientists that
Speaker 9: some of the most powerful companies in the world are
Speaker 9: looking at this right now working on this. For some
Speaker 9: of them this would be great news. For others it
Speaker 9: would be a disaster. So they'll be definitely testing out
Speaker 9: the veracity of this, and I think the actual where
Speaker 9: the truth lies will emerge with a bit more time.
Speaker 5: In What do you make of selloffs in other names
Speaker 5: today Broadcom, for example, Marvel, I mean everybody is getting
Speaker 5: hit in the sector. As Carol mentioned, twenty eight of
Speaker 5: thirty names lower.
Speaker 9: I mean, yeah, yeah, the logic is absolutely clear, right,
Speaker 9: I mean, if you are no longer a believer in
Speaker 9: this exponential growth in spending, in this exponential need for
Speaker 9: more and more computing, then you're going to sell Micron,
Speaker 9: You're going to sell broad Coom, you're going to sell Marvel,
Speaker 9: and of course you're going to sell in video or
Speaker 9: you know. The logic based upon an assumption, and that's
Speaker 9: what it is at this point is flawless. I mean,
Speaker 9: for example, Broadcom, they are the key ingredient in terms
Speaker 9: of these companies like Google that are now designing their
Speaker 9: own chips for this type of purpose. So if there's
Speaker 9: going to be less need for that kind of high
Speaker 9: end chip, then it makes sense to sell them.
Speaker 3: I mean, none of this happens in a vacuum, right,
Speaker 3: so I can only imagine the meetings that are happening
Speaker 3: at Nvidia today and all of the chip companies. So
Speaker 3: would you expect them to, you know, you know, tear
Speaker 3: apart the research from this and try to understand exactly
Speaker 3: what they did and then come back with their own response.
Speaker 9: You've got I mean, they've got to do that, right,
Speaker 9: I mean, the the you know, if this was a
Speaker 9: two or three percent move and a few market jitters.
Speaker 9: Then you know you probably as a management team you
Speaker 9: look into it fiercely, but you just keep your mouth shut.
Speaker 9: Or we're just about to go into earning season, right,
Speaker 9: So whether they like it or not, for example, Intel
Speaker 9: on Thursday are trying to get into this market, They're
Speaker 9: going to get asked about this.
Speaker 10: What have you got?
Speaker 9: How can you deal with this? Is this good for you?
Speaker 9: These are all questions that I think, you know, everybody's
Speaker 9: companies are going to be answering over the next two
Speaker 9: or three weeks, and they better have some good answers.
Speaker 5: And do folks you taught you speak to who are
Speaker 5: covering the industry, have they been waiting for a day
Speaker 5: like today?
Speaker 10: Like was this bound to happen?
Speaker 9: I mean, you know, investors do two things right. You
Speaker 9: have different types of investors, but basic pattern recognition is
Speaker 9: supposed to be the skill that everybody can bring to this,
Speaker 9: whether your technical or whether you're just a you know,
Speaker 9: a general investor. So I think a lot of the
Speaker 9: general investors will be like, let's let's not be on
Speaker 9: the wrong side of what happened in two thousand with
Speaker 9: all of the Internet sell off. Let's get out right now, right,
Speaker 9: maybe we're at the peak. More sort of technically savvy
Speaker 9: investors will probably take their time look at this and
Speaker 9: try to find out just how much truths there is
Speaker 9: there and just how many concrete implications there are.
Speaker 7: Well in terms of implications too.
Speaker 3: You know, a lot of what's been kicked around throughout
Speaker 3: the day is you know, I feel like TikTok, you know,
Speaker 3: version two point zero in other words, another Chinese company.
Speaker 3: You know, you want to know how much the government
Speaker 3: is involved and how much maybe you know, do they
Speaker 3: support the r indeed, siphius from the United States, the
Speaker 3: Committee on Foreign Investment in the United States, you know,
Speaker 3: are they going to weigh in on this whether or
Speaker 3: not you know, American companies or you know, can tap
Speaker 3: into it. I mean, it's a whole other round of this,
Speaker 3: it seems.
Speaker 11: Yeah.
Speaker 9: No, I clearly there's a lot of scrap rambling going on.
Speaker 9: And you know, the path that's happened so far in
Speaker 9: that particular area has been to restrict access to these
Speaker 9: high end chips. So guess what, the country that is
Speaker 9: restricted from these high end chips suddenly comes up with
Speaker 9: the magic bullet solution, which says, maybe we don't need
Speaker 9: as many of these high end chips, or maybe we
Speaker 9: don't need them at all. So there is an element
Speaker 9: of like, hmm, okay, is this really Is this the
Speaker 9: answer that they want us to be concerned about, or
Speaker 9: is this really the answer? Or have we given them
Speaker 9: so much incentive to find a way around it that
Speaker 9: they've poured all their energy into it being really smart
Speaker 9: and got around it. I mean, layers upon layers of
Speaker 9: things going on here, but in general, there are no
Speaker 9: magic bullets in at least the chip industry. It tends
Speaker 9: to be a pretty incremental industry where we see changes
Speaker 9: over time. Software can be more volatile and you know,
Speaker 9: is prone to more kind of instant changes in thinking.
Speaker 9: But even then, and you know, the change to a
Speaker 9: whole industry, the direction that's going in, it's a little
Speaker 9: bit hard to imagine that one morning we all wake
Speaker 9: up and go, oh dear right. But at the same time,
Speaker 9: if you're an investor, you can't afford to ignore the possibility.
Speaker 9: And if you're the CEO of in Video or the
Speaker 9: board of InVideo or the senior management of video, you
Speaker 9: cannot afford to ignore the possibility.
Speaker 5: Ian on a day like today, you know, we're certainly
Speaker 5: focused on the big names that are moving lower by
Speaker 5: double digits in video, certainly down Broadcom is lower today,
Speaker 5: Oracles down by fourteen percent.
Speaker 10: But from a.
Speaker 5: Hardware perspective and from Deep six perspective, what do you
Speaker 5: know about the hardware that Deep seek users to train
Speaker 5: its own?
Speaker 9: That's no, and that's that's a very good question. That's
Speaker 9: probably one that the US government are looking into, which is,
Speaker 9: you know, some of the analysis that we've seen has
Speaker 9: been like, look, yes, this model that they're citing that's
Speaker 9: actually a derivative of another model. How did they train
Speaker 9: that original model? So should we classify this derivative model
Speaker 9: that they're offering up as part of this larger equation
Speaker 9: which they must have developed with Western technology? And the answer,
Speaker 9: simple answer is we do not know. And there's going
Speaker 9: to be a lot of pressure on those that need
Speaker 9: to know and should know to find that out. And
Speaker 9: I think we're going to see a lot of reporting emerge.
Speaker 9: We're going to see the government looking into this to
Speaker 9: find out what did they have access to, should they
Speaker 9: have had access to it, if what they had access
Speaker 9: to was in fact more efficient computing than what say,
Speaker 9: Microsoft is putting in place. Then wow, here we go. Right,
Speaker 9: this is a breakthrough so many layers to this onion,
Speaker 9: and that's not a very useful conclusion, but I think
Speaker 9: it's the best that we can offer at this particular point.
Speaker 7: A lot of questions still out there. Ian, Thank you
Speaker 7: so much, so appreciated. Of course.
Speaker 3: Our Bloomberg News US Semiconductor and Networking reporter.
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Speaker 3: It feels like the last week or so, topped off
Speaker 3: by today's news on Deep Seek, has put the AI
Speaker 3: story once again tim front and center in a super
Speaker 3: big way.
Speaker 10: Yeah.
Speaker 5: Remember just last week, President Trump any group of tech
Speaker 5: companies SoftBank, Oracle and open Ai initially planning to invest
Speaker 5: one hundred billion dollars to build US based infrastructure, including
Speaker 5: data centers for open Ai, the project we know called Stargate.
Speaker 5: On that though, one very high profile tech and administration
Speaker 5: voice who's not all in on it It's something that
Speaker 5: Bloomberg BusinessWeek columnist Max Chaffkin gets into in his latest
Speaker 5: story and in the latest Bloomberg BusinessWeek daily newsletter. You
Speaker 5: can read Max's business Week story on the Bloomberg and
Speaker 5: at Bloomberg dot com slash BusinessWeek. Max the co host
Speaker 5: of the Lining podcast, also the author of the concheriont
Speaker 5: Peter Tiel in Silicon Valley Pursuit of Power. Max, We're
Speaker 5: gonna talk about elon Stargate in just a second, but
Speaker 5: deep Seek is where I want to start because it's
Speaker 5: what's hitting the tech names today. Well, I don't want
Speaker 5: to say all tech names. It's what's hitting you know, Nvidia,
Speaker 5: Broadcoms and of the other chip names in a big
Speaker 5: way today.
Speaker 12: How are you looking at absolutely well, you know, as
Speaker 12: you're hinting at with this discussion of stargate, until basically
Speaker 12: this weekend, you know, AI infrastructure was seen as.
Speaker 6: The end all be all.
Speaker 12: You know, they were talking about not not one hundred billion,
Speaker 12: five hundred billion, right and at times Sam Altman has
Speaker 12: said he's gonna he's gonna need seven trillion dollars in
Speaker 12: you know, funding for AI infrastructure, and there's been this
Speaker 12: sense especially among Google, Open Eye, a bunch of these
Speaker 12: big players, that this is gonna be the thing that
Speaker 12: like only hyperscalers are going to be able to compete
Speaker 12: in that whoever has the most infrastructure, even whoever has
Speaker 12: the most power. Right, We've seen a big run up
Speaker 12: in nuclear stocks and things like that, so so, and
Speaker 12: this sort of threw all that out the window because
Speaker 12: if we're to believe what deep seek is saying, this
Speaker 12: was done with a much much lighter weight, uh you know,
Speaker 12: amount of usage of chips and it and it actually
Speaker 12: is running a lot more efficiently efficiently. So that suggests,
Speaker 12: right that that these this crazy run up we've seen
Speaker 12: in demand for GPUs and so on might be overheated.
Speaker 12: And we we had other reasons to think that there
Speaker 12: was perhaps some sort of bubble or a little bit
Speaker 12: of frothiness in this market. And and I do think
Speaker 12: if it hadn't been this, it might have been something else.
Speaker 10: Right.
Speaker 6: I think investors were and are primed.
Speaker 12: To see, you know, to see to see potential flaws
Speaker 12: and with the with the business model that so many
Speaker 12: have bought into.
Speaker 3: So not necessarily an end of like the AI spend,
Speaker 3: but just kind of a twist and turn in the story.
Speaker 3: And there's still more to be known, right Max, in
Speaker 3: terms of the reliability of the information we're hearing from
Speaker 3: them and the reality of it.
Speaker 12: Yeah, there's so much we don't know here, and again
Speaker 12: it's definitely worth I think approaching Deep Seek's claims skeptically
Speaker 12: and also understanding that there if they were able to
Speaker 12: develop a much more inexpensive model that could help parts
Speaker 12: of the AI market. It doesn't necessarily mean that all
Speaker 12: of this goes away or something, but it may.
Speaker 7: Make it more accessible, right, that's less expensive.
Speaker 12: Yeah, it definitely, but it could cause investors to like
Speaker 12: dramatically revalue like some of their assumptions.
Speaker 5: How does it change the narrative around what China is
Speaker 5: able to do when it comes to AI right now
Speaker 5: and sort of the tech race that's happening there. The
Speaker 5: thing is, if they weren't supposed you know, there are
Speaker 5: these chips, A lot of these chips are not supposed
Speaker 5: to go to certain parts of the world.
Speaker 12: Right, So that so there's something potentially troubling there. If
Speaker 12: you're if you're looking at the attempts to restrict certain
Speaker 12: US technology to China, it seems like either those restrictions
Speaker 12: aren't working that well, maybe some GPUs found their way
Speaker 12: to China, or or that the Chinese software industry has
Speaker 12: found ways around it, which would also be potentially problematic,
Speaker 12: I suppose from a sort of US national security perspective,
Speaker 12: at least from the point of view of the China
Speaker 12: Hawks who have been sort of warning about this, and
Speaker 12: that includes many of the Silicon Valley companies like remember,
Speaker 12: one of the big reasons to justify this, like massive
Speaker 12: spend on AI And one of the reasons that many
Speaker 12: of these folks, including Sam Altman, sees this as a
Speaker 12: thing that government should be involved in, is because they
Speaker 12: have been arguing that without this, without spending huge sums
Speaker 12: of money on say on power or investing in infrastructure
Speaker 12: in terms of data centers, that we would fall behind
Speaker 12: behind the Chinese tech startups. And that may you know,
Speaker 12: if you sort of extrapolate from this very small piece
Speaker 12: of news, you might say, Okay, well it's happening anyway.
Speaker 12: So that sort of throws everything into a bit of disarray.
Speaker 7: All right, So let's get to stargate. Love the name,
Speaker 7: love the name Elon Musk. I find it interesting. I
Speaker 7: think we all found it interesting.
Speaker 3: That here's this big announcement right that comes out of
Speaker 3: the Trump administration last week, and Elon not so in
Speaker 3: on it?
Speaker 6: Is he no, not in on it at all.
Speaker 12: You know, it wouldn't be surprising if if you had
Speaker 12: this big announcement with Donald Trump and the CEOs of
Speaker 12: some major companies talking about huge numbers, right they were saying,
Speaker 12: we're going to invest one hundred billion dollars immediately five
Speaker 12: hundred billion with the next four years, would not have
Speaker 12: been surprising if some people said this sounds like a
Speaker 12: political stunt, I'll believe it when I see it. It's
Speaker 12: what made this thing that happened last week so surprising
Speaker 12: is that the person saying that was a senior advisor
Speaker 12: to Donald Trump, and it was Elon Musk.
Speaker 6: Tweeting over and over and over again last week.
Speaker 12: I mean, the last time I checked, twenty times, he's
Speaker 12: tweeted a few more times. You know, the usual mix
Speaker 12: of i'd say, off color jokes and put downs. You know,
Speaker 12: he's called Sam Altman, who was of course on stage
Speaker 12: with Donald Trump, a swindler. He suggested the announcement was fake,
Speaker 12: and Trump has sort of responded by saying, hey, you
Speaker 12: know Elon Musk has a dispute with one of the
Speaker 12: people in this in this deal, which is true.
Speaker 6: Sam Altman and Elon Musk have.
Speaker 12: Been feuding more or less in public for the last
Speaker 12: couple of years, So we're sort of seeing I'd say,
Speaker 12: you know, maybe one of the downsides to having somebody
Speaker 12: who is as deep in the business world also involved
Speaker 12: as a advisor to the president.
Speaker 5: I mean, is Elon Musk at this point saying, Hey,
Speaker 5: I gave you some giant bags of money to help
Speaker 5: you win the election.
Speaker 7: What were you thinking?
Speaker 5: And now you're doing this? Does this risk driving a
Speaker 5: wedge between the two of them?
Speaker 6: I think for both Musk and Trump.
Speaker 12: I mean, there has been over the last couple of
Speaker 12: months people who have been hot on high alert for
Speaker 12: signs that this relationship might be might be breaking up.
Speaker 12: And I would say that it doesn't seem like this
Speaker 12: has done it either. You know, you know, Trump has
Speaker 12: cracked jokes before, We've seen these tweets. There have been
Speaker 12: there was a dispute over the H one B visa
Speaker 12: thing both Musk.
Speaker 5: And maybe that led to the divorce between Ramaswamy and Musk.
Speaker 12: Yeah, yeah, at least according to some reports. You know,
Speaker 12: it's possible there are other reasons as well. But but
Speaker 12: what I'll say is it seems like Musk and Trump
Speaker 12: are still working closely together. I'd say Trump's comments about
Speaker 12: this to me suggested that he was untroubled by Musks,
Speaker 12: you know, apparently kind of trying to undermine or or
Speaker 12: undermine some of his partners in this deal. And I'd
Speaker 12: say part of that is that, you know, there's not
Speaker 12: necessarily government money going into this. In the Stargate thing,
Speaker 12: it really was basically a media event for Donald Trump
Speaker 12: to announce a big business deal so that he can
Speaker 12: claim credit for, you know, helping to spur the economy.
Speaker 12: It's kind of like a vibes thing. And I think
Speaker 12: because of that, I'm not sure it really hurts Trump
Speaker 12: all that much to see Elon Musk dissing Sam Altman
Speaker 12: on Twitter.
Speaker 3: Well, you write in your story, Max, you said Musk
Speaker 3: has always treated his conflicts of interest like features rather
Speaker 3: than bugs, seeming to run his normally independent companies with
Speaker 3: their nominally independent shareholder basis as if they were a
Speaker 3: single conglomerate. You talk about employees being lent out, sharing
Speaker 3: of resources and stuff.
Speaker 7: So conflict he's kind of all in on this too.
Speaker 12: Well, yeah, absolutely, this is a big part of First
Speaker 12: of all, competing in this area is a big part.
Speaker 6: Of Elon Musk's big plan for.
Speaker 12: His companies, not just Tesla, which of course is developing
Speaker 12: you know, advanced robotics and is trying to build self
Speaker 12: driving cars, but also x Ai, his his chatbot competitor,
Speaker 12: so he is very much playing in this market. He
Speaker 12: is also competing to buy these Nvidia these high end
Speaker 12: in Nvidia GPUs. He's building giant data centers, so he
Speaker 12: very much has a dog in this fight, and that's
Speaker 12: why he's doing this. And I think Trump's attitude seems
Speaker 12: to be that's all out in the open, as long
Speaker 12: as people understand that what's behind this is a business dispute.
Speaker 6: Again, he said, well, one of the things is.
Speaker 12: Is he hates one of the guys in the deal,
Speaker 12: an obvious reference to Elon Sewings and but then Trump said,
Speaker 12: you know, I hate people too.
Speaker 7: So we all have a problem.
Speaker 11: Child.
Speaker 5: I wonder you know what what Donald Trump has been
Speaker 5: able to do in recent months has been pretty incredible
Speaker 5: when it comes to the tech industry. I mean a
Speaker 5: week ago, Carol and I were sitting here looking at
Speaker 5: the stage and during the inauguration, and you saw titans
Speaker 5: of industry who were not at previous inaugurations there all
Speaker 5: collectively getting behind the president. I mean, he's he is
Speaker 5: this larger than life figure who perhaps can bring people
Speaker 5: together who don't like each other, maybe because he offers
Speaker 5: them something that they want.
Speaker 12: Yeah, well, Trump probably more so, at least than than
Speaker 12: foreign President. Biden approaches the presidency in a way that
Speaker 12: I think would be fair to describe as a little
Speaker 12: bit more transactional.
Speaker 11: Right.
Speaker 12: He's willing to bend his policies to make deals. It's
Speaker 12: the whole thing that he's about, and in certain ways,
Speaker 12: right that works well for CEOs.
Speaker 6: I also think there's a lot going on there.
Speaker 12: There was a lot of built up anger in Silicon
Speaker 12: Valley over some of Biden's policies over anti trust for instance,
Speaker 12: and you have a lot of opportunism right now. There's
Speaker 12: a sense that they have leverage because by showing up
Speaker 12: in these Trump things, they they're giving Trump some additional
Speaker 12: credibility and they're trying to use that to get you know,
Speaker 12: what they can, which is, you know, favorable policies, favorable
Speaker 12: and trust policy.
Speaker 7: We're going to talk about that in the next couple
Speaker 7: of hours.
Speaker 5: Hey Max, do you want to go back to where
Speaker 5: we started and deep Seek because we're getting some breaking
Speaker 5: news and video is out saying that deep seek is
Speaker 5: quote excellent AI advancement and says that deep Seek's work
Speaker 5: quote fully export control compliant and says that inference requires
Speaker 5: significant numbers of its GPUs. This is an email statement
Speaker 5: on the deep seek AI model. They're they're coming out
Speaker 5: and saying talking about it. I'm wondering how you view that.
Speaker 12: I mean, I think it's first of all, everybody's talking
Speaker 12: about it. It seems like it seems like they that
Speaker 12: they have to and they also I think in that
Speaker 12: statement and I haven't looked at I'm just hearing it now,
Speaker 12: it seems like an attempt to address suggestions that perhaps
Speaker 12: deep seat Seek had access to you know, improper access
Speaker 12: to GPUs or something like that.
Speaker 6: It sounds like they are saying, no, that's not the case.
Speaker 12: Again, it definitely seems like this would be a business
Speaker 12: challenge for for Nvidio if you were if you were.
Speaker 6: Able to do the kinds of hatbot.
Speaker 12: You know, work much much more efficiently with about the
Speaker 12: same sort of level of quality that's gonna make these
Speaker 12: GPUs perhaps not as valuable.
Speaker 6: But again a lot. There's a lot here that we
Speaker 6: don't know.
Speaker 12: And you also have seen people on the other side
Speaker 12: of this saying, actually, this is going to be great
Speaker 12: because it's gonna make these chatbots so much cheaper. We're
Speaker 12: gonna see tons of them. Essentially, we're gonna make it
Speaker 12: up on volume. It's hard to know how to evaluate that,
Speaker 12: and we don't know that much about how this was
Speaker 12: put together or really just how good the quality looks.
Speaker 12: People have been playing with it only for a short amount.
Speaker 3: Wait you want details. Excilly you great stuff, Max, Thank
Speaker 3: you so much. Bloomberg Business Week commnist Max Chafkin is
Speaker 3: also co host of the Elon Inc.
Speaker 7: Podcast.
Speaker 13: You could check that out.
Speaker 3: It's on the Bloomberg and also at Bloomberg dot com
Speaker 3: slash Elon Inc. Max is also author of the contrarian
Speaker 3: Peter Teel and Silicon Values Pursuit of Power.
Speaker 2: This is the Bloomberg Business Week podcast. Listen live each
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Speaker 3: Hey, I guess say reading in this morning, Morgan Stanley
Speaker 3: continues to recommend that investors hold long five year treasuries
Speaker 3: ahead of two potentially devish market catalysts. And those catalysts
Speaker 3: are the January FED meeting, So not this week's meeting
Speaker 3: and then this month's job report. Meantime, you've got jp
Speaker 3: Morgan stay staying along the front end of the treasury
Speaker 3: curve well Bimo positioning for two quarter point FED cuts
Speaker 3: this year. So while we are focused so much tim
Speaker 3: on tech and AI news this morning, let's not forget
Speaker 3: we at the first FED decision of twenty twenty five,
Speaker 3: That decision out on Wednesday.
Speaker 10: Okay, with more on that, With.
Speaker 6: More on that.
Speaker 5: In the studio, we got Ian Wyatt's senior vice president
Speaker 5: director of Economics at Huntington Commercial Bank. It's a division
Speaker 5: of the publicly held roughly twenty five billion dollar market
Speaker 5: cap Huntington Bank. Shares Ian, good to see you. Look
Speaker 5: before we jump been to exactly what we're going to
Speaker 5: hear from Fed sho Jpowell, I would imagine he might
Speaker 5: get some questions around AI and the market sell off
Speaker 5: this week. Whether or not he answers those questions, that
Speaker 5: certainly remains to be seen. I would figure out a
Speaker 5: way to ask him a question around that, How do
Speaker 5: you think, how are you looking at what's happening in
Speaker 5: the market this week, especially ahead of this FED meeting?
Speaker 14: I think, well, first, I think in terms of the
Speaker 14: FED meeting, not related to AI, I think long our
Speaker 14: view is that there's still inflationary pressures out there in
Speaker 14: the economy when I taught, but I think it's really
Speaker 14: we have this two speed labor market we're seeing. We're
Speaker 14: seeing is for lower end jobs. You know, where's the
Speaker 14: job growth been. It's been restaurants, it's been hotels, It's
Speaker 14: been a lot of service areas. And when I talk
Speaker 14: to companies in those areas, whether you're manufacturing, transportation, still
Speaker 14: a tight labor market. They're having a hard time finding workers.
Speaker 14: If you're talking about more of a college job, professional
Speaker 14: and business services, where are we not getting job growth?
Speaker 10: It obviously has been down.
Speaker 14: We've seen you know, them focusing on cash flow more
Speaker 14: than job growth. So we kind of have this this
Speaker 14: two speed labor market where you still have a tight
Speaker 14: lower end, and the problem for inflation is a lot
Speaker 14: of those industries are very labor intensive.
Speaker 10: You know, childcare for example.
Speaker 14: It's something where labor or restaurants, labor makes up a
Speaker 14: huge percentage of your cost structure, and they're still feeling that pressure.
Speaker 14: So I think we've probably been on the low end
Speaker 14: of the FED saying in terms of cuts for twelve
Speaker 14: months now. Yeah, now I think we're more in line
Speaker 14: with the two cuts roughly this year. But I still
Speaker 14: think that pause holds for a while because I think
Speaker 14: there is that fundamental underlying inflationary pressure that is not
Speaker 14: really when you tease out inflation, you look category by category.
Speaker 10: It's not been durable goods.
Speaker 14: Durable goods have been coming down, but it's also stuff
Speaker 14: that consumers can choose not to buy.
Speaker 3: So I just want to stay with AII for a moment.
Speaker 3: That AI spend the economic you know, activity, it may
Speaker 3: impact on the upper down side. You know, how does it,
Speaker 3: if at all, factor into any of your ex economic
Speaker 3: models when it comes to growth, when it comes to inflation,
Speaker 3: and then ultimately to FED policy.
Speaker 14: You know, AI caused me to get one call really
Speaker 14: wrong last year. It was I thought construction employment was
Speaker 14: going to come down. Yeah, I thought, you know, multifamilies
Speaker 14: coming down. We saw warehouse space is over supplied. Now
Speaker 14: obviously office has its issues, and I underestimated how much
Speaker 14: it would be chipsacked.
Speaker 10: It would be the.
Speaker 14: Chip plants like Columbus for example, or we're headquartered. They
Speaker 14: have that massive intel plant, a couple of the largest
Speaker 14: cranes in the world operating there. And AI was a
Speaker 14: huge part of this. And I still think there's this
Speaker 14: huge first mover advantage. You don't want to be the
Speaker 14: last company. You want to be the last company that
Speaker 14: still gets a power connection versus the first where they
Speaker 14: say no, we don't have enough juice, we can't afford
Speaker 14: or we can't build, you know, connect you for five years.
Speaker 10: And I think that that case still remains.
Speaker 6: Yeah.
Speaker 14: I also think there's another bullish case for power that
Speaker 14: when you look at the forecasts and really baked invert.
Speaker 10: What is that about? Transportation?
Speaker 14: So so, okay, if you look at US energy consumption,
Speaker 14: roughly fifteen percent of US energy consumptions residential, that's what
Speaker 14: we always think of our power. Thirty seven percent of
Speaker 14: US energy consumption is transportation. Right now, over the last
Speaker 14: six months roughly ten percent of US car sales we're
Speaker 14: up to have been plug in vehicles now. Vehicle fleet
Speaker 14: takes a long time to turn over in the US
Speaker 14: average vehicle ages over twelve years now, it takes a while.
Speaker 14: But as that starts to kick in, if EVE even
Speaker 14: got a small fraction of that thirty seven percent shifting
Speaker 14: from fossil fuels to electric power, it doesn't really matter.
Speaker 10: The source, whether it's gas or solar.
Speaker 14: Or whatever, you have a very different outlook for electric
Speaker 14: demand at the US. And I think that also means
Speaker 14: utilities are going to have to build a ton of infrastructure.
Speaker 5: Does that get derailed by the Trump administration pushing back
Speaker 5: against EB subsidies and moving trying to get people to
Speaker 5: move away from evs.
Speaker 14: I mean, I think it slows it to some degree.
Speaker 14: I think that's definitely. You know, you're seeing a shift
Speaker 14: administration policy. If you look at Germany, for example, when
Speaker 14: they cut their TV subsidies, that dramatically slowed EV's sales.
Speaker 14: But it's still something where there's a lot of the
Speaker 14: global market is shifting in that direction. Autos are shifting
Speaker 14: that way.
Speaker 7: China's all in, China's all in.
Speaker 14: I mean, you talked to a friend of mine runs
Speaker 14: FedEx distribution, owns a couple of Fredecks distribution places, and
Speaker 14: he talks about, you know, the gas prices on his
Speaker 14: delivery trucks, and he's really looking, how do I lower
Speaker 14: my fuel expenses? And that's really a perfect application for
Speaker 14: EV short range so stop start driving?
Speaker 10: So does he do that with Rivians?
Speaker 14: Like yeah, I mean he's looking at Yeah, he's looking
Speaker 14: I mean, Rivian's just starting to sell beyond Amazon now,
Speaker 14: they're just moving beyond Amazon or filling those initial orders,
Speaker 14: whether it's that or Forward and Stillantis both have products
Speaker 14: in that market as well.
Speaker 10: Sorry here, I know we're supposed to be talking about.
Speaker 3: The I kind of love this because it's a fuller
Speaker 3: picture of kind of the markets and really our economy.
Speaker 3: So having said that, I mean, I don't know this
Speaker 3: January meeting, the decision on Wednesday Ian, is it kind
Speaker 3: of a snoozer because we don't really expect anything? Or
Speaker 3: is there a fine noodle, a noodle, a fine needle
Speaker 3: that j Powell has to thread here?
Speaker 14: In some ways I think thematically we've seen you know,
Speaker 14: a year ago when he did the Palll pivot, you
Speaker 14: felt like there was pushback right after he spoke at
Speaker 14: that presser, and it definitely seemed like he was on
Speaker 14: the duvish end of the spectrum. If you look back
Speaker 14: at the September vote on the dot plot, you can
Speaker 14: see almost half of Fed Governor's only wanted three cuts
Speaker 14: this fall. So that would mean essentially there should have
Speaker 14: been one twenty five in each meeting, and that meant
Speaker 14: they were opposed to fifty in September. Now, obviously they
Speaker 14: all get in board, they all push in the same direction,
Speaker 14: but if you look at the minutes, you look at
Speaker 14: the notes, I think he's still again. I think this
Speaker 14: is a repeat of about a year ago. It's he's
Speaker 14: on the dubvish end of the spectrum. He has to
Speaker 14: get the board to come along with him. And I
Speaker 14: don't think I think. I think the inflationary pressure is
Speaker 14: still there. I still think there's some underlying and when
Speaker 14: I talk to companies in the economy, depending on the
Speaker 14: part of the labor market they're in.
Speaker 10: It's still there.
Speaker 14: It's it's still significant, and I think that helps some
Speaker 14: of the more hawkish voices on the FED, where the
Speaker 14: very narrowly balanced FED I think on this.
Speaker 3: So it's really labor costs that you're most concerned about.
Speaker 3: It's not the price of eggs that everybody keeps talking about.
Speaker 3: It's really labor costs.
Speaker 14: Well, yeah, I mean, I'm the grocery shopper in the family,
Speaker 14: so I definitely noticed the price of eggs. And I
Speaker 14: know used to work in Georgia, so I know, you know,
Speaker 14: top egg economy, top egg producing state in the country
Speaker 14: is basically offline right now because of bird flu. So
Speaker 14: there's some big things going on there. But now I'm
Speaker 14: much more concerned about rent growth. I mean, that's a
Speaker 14: good sign we're seeing on the inflationary front. If you
Speaker 14: look at the market based rent indexes, you can see
Speaker 14: you're at one one and a half percent. The problem is,
Speaker 14: you know, two thirds of Americans on their home A
Speaker 14: lot of that single family we're still seeing and the
Speaker 14: implicit rent deflator from that comes from rents on single family,
Speaker 14: not multi family, and that's still feeling pressure.
Speaker 7: What did you want to say, I know I jumped in.
Speaker 5: Oh, I just I wanted to just say in videos
Speaker 5: down eighteen percent, everybody, that's the that's the day. Looking
Speaker 5: at Broadcoms down eighteen percent, Oracles down seventeen.
Speaker 7: Percent, but no inflation there.
Speaker 10: Then that's a backdrop of some would say.
Speaker 3: It's on sale or maybe not, depending on the outlook.
Speaker 3: This was really fun. Come back soon and why are
Speaker 3: senior vice president and director of economics loved where the
Speaker 3: economic conversation went over at Huntington Commercial Bank.
Speaker 7: Joining us here Tim in studio.
Speaker 1: You're listening to the Bloomberg Business Week podcast. Catch us
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Speaker 5: Susy dan Is Cudy of America's over at Wi Bro.
Speaker 5: It's a global consulting firm that provides services related to
Speaker 5: IT cloud and yes AI. And that's really what we
Speaker 5: want to talk to her about because that is why
Speaker 5: we're seeing the selloff concern that a cheaper AI model
Speaker 5: from the Chinese startup Seek could make valuations of these
Speaker 5: tech that has powered the bull market pretty tough to justify.
Speaker 5: It's what we spoke to Gena Martin Adams about just
Speaker 5: a minute ago. Suzanne joins us from East Brunswick, New Jersey. Susanne,
Speaker 5: you are just back from Davos, where we know AI
Speaker 5: was front and center. Given comments that we areed from
Speaker 5: Alexander Wong, who is the founder at CEO over at
Speaker 5: Scale AI, how would you though characterize the AI conversation
Speaker 5: that was happening over at Davos.
Speaker 11: Well, thank you both for having me. Everything was AI
Speaker 11: last week. You could walk down the street and every
Speaker 11: storefront had something about AI or was talking about AI.
Speaker 13: So it was front and center.
Speaker 11: This is clearly a defining year for AI and for
Speaker 11: jen AI, and businesses are looking to figure out how
Speaker 11: do they drive value from this. Most CEOs believe that
Speaker 11: it's going to significantly change the way they do business
Speaker 11: in terms of how they create and deliver value and
Speaker 11: obtain value from the work that they do. And there
Speaker 11: was a clear momentum around, you know, defining the strategy
Speaker 11: in which they're going to invest in AI to create
Speaker 11: that value.
Speaker 3: Why do you think it's that they were saying or
Speaker 3: why is it that this is going to be a
Speaker 3: defining year, especially on a day when we kind of
Speaker 3: just got you know, a company that might say, hey,
Speaker 3: you don't need to do the big span or you know,
Speaker 3: we can do it. It's a different maybe financial model
Speaker 3: in terms of the buildout, I feel like we're still
Speaker 3: kind of finding our way. So why why is it
Speaker 3: that twenty twenty five is the defining way. I'm not
Speaker 3: quite sure how to read that.
Speaker 13: Well.
Speaker 11: I think last year everybody was talking about AI and
Speaker 11: just piloting with genai. It was, you know, it became
Speaker 11: it's democratized. Everybody has access to it, we can use it.
Speaker 11: I think the GENAI races and during a new phase.
Speaker 11: We saw it this morning and I think we're still
Speaker 11: in the beginning, you know. To me, it really calls
Speaker 11: to everyone that this emphasizes the pace we're going to
Speaker 11: see innovation and really figuring out how we can create
Speaker 11: agile and environments to deliver on AI. And at the
Speaker 11: end of the day, it's going to be about the
Speaker 11: quality of the data that these AI are trained on
Speaker 11: and deliver for our clients to really deliver value to
Speaker 11: the organizations, regardless of how much they spend. And I
Speaker 11: think you know where we see it is our clients
Speaker 11: really are talking about the data they need to fuel AI,
Speaker 11: whether it's a large language model or a small one.
Speaker 5: I'm just just for context, because we do speak to
Speaker 5: a lot of folks who run consulting firms or run
Speaker 5: parts of consulting firms. Just give us an idea of
Speaker 5: your clients, the type of clients you have, and you
Speaker 5: know who's out there working with you.
Speaker 13: Yeah, so I work, so my responsibility.
Speaker 11: I have clients across financial services, oil and gas, energy
Speaker 11: and utilities, high tech, and manufacturing and automotive. So I
Speaker 11: have clients across many different industries and many different challenges
Speaker 11: that can be solved with them without AI.
Speaker 5: So who would you say is leveraging AI the best
Speaker 5: right now?
Speaker 11: Well, you know, AI is a proven and it's been
Speaker 11: around for ten years. We've been using in AI, and
Speaker 11: many of our financial service as clients have been using
Speaker 11: AI and machine learning models for years. It's only now
Speaker 11: with GENAI we're seeing this acceleration and that's what's truly
Speaker 11: exciting is how we can leverage the genai applications. You know,
Speaker 11: we've been also leveraging it internally so that we can
Speaker 11: learn and then deliver those learnings to our clients. We're
Speaker 11: leveraging in HR, we're leveraging it illegal across the board
Speaker 11: to make sure that we understand how AI can be
Speaker 11: used and understand the foundation and the governance and responsible
Speaker 11: nature in which we need to deploy it and train
Speaker 11: our people to make sure that it's successful.
Speaker 3: So, Susan, what I'm wondering is like on a daylight today,
Speaker 3: where this story a company that nobody had really are
Speaker 3: I should say nobody because our Bloomberg intelligence teams like, yeah,
Speaker 3: our team overseas has been writing about deep Seek for
Speaker 3: you know, the last couple of years, so it's not
Speaker 3: necessarily new to them, but certainly new to I feel
Speaker 3: like our conversations when it comes to AI in general.
Speaker 7: So I am.
Speaker 3: Curious, have you guys your team, you know your phone's
Speaker 3: been ringing today's say, wait, what is this deep Seek?
Speaker 3: And you know I've been spending X on my AI
Speaker 3: infrastructure build or you know, making plans? Do I need
Speaker 3: to rethink it? Do I not need to spend as much,
Speaker 3: you know, on site versus not? You know what tell
Speaker 3: us about today and the conversations perhaps that you guys
Speaker 3: have all been having.
Speaker 11: So today it's all over the news. It's absolutely correct,
Speaker 11: everyone's talking about it. I think the reality is over
Speaker 11: time there's going to be winners and losers. You know,
Speaker 11: the role that we play is helping our clients make
Speaker 11: sure they have the foundations in place. One of the biggest,
Speaker 11: and I'll go back to it, is the data.
Speaker 13: And the people.
Speaker 11: You know, training your teams to think about AI first
Speaker 11: and how to bring AI into a business to add value,
Speaker 11: so it could make an AGENC that could do make
Speaker 11: autonomous decisions and be managed appropriately. The data foundations, so
Speaker 11: the models don't hallucinate. All that has to be done
Speaker 11: regardless of the technology that you choose. So that's where
Speaker 11: I think the real area that we can add value
Speaker 11: in helping our clients navigate both the frameworks, the governance,
Speaker 11: the training of the people, all the change management, and
Speaker 11: the data.
Speaker 13: All that still has to happen regardless.
Speaker 11: Of which model that you choose to use and the
Speaker 11: foundations you build on.
Speaker 7: So the spend is going to still happen. Nobody's going
Speaker 7: to put back.
Speaker 11: Yeah, I think it'll depend on what the use cases
Speaker 11: and what the spend will be. So I think that
Speaker 11: is yet to be determined, depending on the models that
Speaker 11: our clients use. And many of our clients are using
Speaker 11: large models, and many of our clients are using their
Speaker 11: data and developing small models. But you know, I do
Speaker 11: think this is a race that is continuing and we're
Speaker 11: going to see this evolution and many more to come.
Speaker 5: Where do you see the actual money savings happening with
Speaker 5: these companies that you work with? Is it from a
Speaker 5: customer service perspective? The whole rise of the AI agent?
Speaker 5: Where do companies where would our margins be helped?
Speaker 13: Yeah? So I think there's two things.
Speaker 11: You know, there's a whole site of productivity and efficiency.
Speaker 11: Seeing that in development, you know, making our developers more
Speaker 11: productive and more efficient, and we're seeing it in testing
Speaker 11: of technology and applications. Absolutely, we're seeing that today. There's
Speaker 11: also things like contact center where we're helping clients in
Speaker 11: servicing and using AI to make the agent smarter and
Speaker 11: delivering higher quality engagement. So there's lots of area where
Speaker 11: we're seeing productivity and efficiency and the question is does
Speaker 11: that translate into our clients being able to add more
Speaker 11: higher value work to those or driving the costs down
Speaker 11: in their business.
Speaker 13: And we're seeing both. You know, we launched just as I.
Speaker 11: You know, one example is whippro now, which is a
Speaker 11: HR intelligent agent and we've put all of our HR
Speaker 11: policies and procedures into this agent and it's serviced over
Speaker 11: eight million queries to date at greater than ninety percent accuracy.
Speaker 11: We've been able to reduce the number of of HR
Speaker 11: employees to service those queries and to service those and
Speaker 11: be able to reap purpose. So you can say that's
Speaker 11: a great efficiency play, but it's also a great employee experience.
Speaker 11: Our employees are able to get real time information, real
Speaker 11: time insights into HR and be able to have a
Speaker 11: better experience than maybe looking for documents in lots of
Speaker 11: flou volders.
Speaker 3: Well, that's what I wanted to ask you. What was
Speaker 3: the kind of satisfaction rate as I play around or
Speaker 3: increasingly am you know, working with chats chatbots to deal
Speaker 3: with service customer service issues. I mean, sometimes it's really
Speaker 3: great and sometimes it's not. So I'm curious from your
Speaker 3: internal team how did it go or what you guys
Speaker 3: have learned in the process, because it's never perfect right
Speaker 3: out of the gate.
Speaker 13: No, it isn't, and it takes time.
Speaker 11: In the early days, you know, the the the quality
Speaker 11: wasn't as good as it is today, and the satisfaction
Speaker 11: is really high. I don't have the specific numbers. I
Speaker 11: know I've used it and it has been great. The
Speaker 11: reality is it's not the chat bots, which is based
Speaker 11: on rules. It's the it's an intelligence agent, so it
Speaker 11: learns over time and we all know.
Speaker 13: That's the power of AI. AM that's what it a
Speaker 13: great experience.
Speaker 11: So when something needs to be adjusted, it can be
Speaker 11: and when there's feedback, it constantly is iterating, so it's
Speaker 11: only getting better over time and becoming that that, you know,
Speaker 11: the most intelligent HR agent it can be. So I
Speaker 11: think overall it's the right direction in terms of creating
Speaker 11: a great employee experience and enabling HR to do what
Speaker 11: they should be doing and taking care of people and
Speaker 11: not just answering simple questions. And I think that makes
Speaker 11: it for a more interesting HR experience for that employee
Speaker 11: as well.
Speaker 5: What about the administration and the role of the Trump
Speaker 5: administration in this. We started the announcement of Stargate last week,
Speaker 5: one hundred billion up to five hundred billion dollars of
Speaker 5: investment from AI companies. What was the conversation happening around
Speaker 5: this administration with regard to AI.
Speaker 13: I'll tell you.
Speaker 11: At Davos, there was optimism around the global economy and
Speaker 11: the resilience as well as the US economy, and overall,
Speaker 11: there was interest around what we're doing around AI as
Speaker 11: well as regulatory policies, and I think overall there was
Speaker 11: really just great optimism in Davos around the US economy.
Speaker 3: So in terms of kind of where we go from here,
Speaker 3: you know you're in it. You guys are doing it
Speaker 3: at your own company, you're working with companies consulting when
Speaker 3: it comes to AI. You know this is your number
Speaker 3: three right that this continues certainly to be an investment theme,
Speaker 3: although taking a big hit in today's session, no doubt
Speaker 3: about it. So top of mind that you think investors
Speaker 3: should be watching out for. And just got about thirty
Speaker 3: forty seconds here.
Speaker 11: Yeah, I see the investment in AI to continue and
Speaker 11: I and you know, I think the speculations is going
Speaker 11: to double in the next couple of years.
Speaker 13: I don't believe that test changed.
Speaker 11: Our clients are investing A and AI, and I think
Speaker 11: today's announcements and what we saw today only emphasizes the
Speaker 11: importance of.
Speaker 13: The innovation moving at pace.
Speaker 11: And I really do believe it shows that those who
Speaker 11: invest now in bringing AI into and learning and experimenting
Speaker 11: and scaling will be the market leaders. It's going to
Speaker 11: disrupt every industry and that's what We're encouraging our clients
Speaker 11: to do to lean in and you know, power their
Speaker 11: organizations with AI. And that's why we've added you know,
Speaker 11: whip Pro powered AI and we really believe us being
Speaker 11: powered by AI will only help our clients be successful
Speaker 11: and implementing in their own business.
Speaker 5: Susan Dad, CEO of America's over at the global consulting
Speaker 5: firm whip Ro, joining us from New Jersey this afternoon.
Speaker 7: Macout you let me drive.
Speaker 12: Oh no, no, no, no, this is not a toy, Judge, Honey, please.
Speaker 11: I.
Speaker 3: Want to drive.
Speaker 4: It's a good question.
Speaker 2: This is the drive to the clothes that plungs for MEFIC.
Speaker 3: On Bloomberg Radio, all right, everybody got about eighteen minutes
Speaker 3: left to end the Monday trade. You are listening and
Speaker 3: watching Bloomberg Business with Carol Master along with Tim Stenovek
Speaker 3: live here in our Bloomberg Interactive Broker studio. You heard
Speaker 3: Charlie and Bill Maloney breaking it down. S ANDP down
Speaker 3: about one point seven percent, the Nawstak one hundred down
Speaker 3: the most when it comes to the index trade looking
Speaker 3: about three point two percent decline here. I am curious
Speaker 3: to see what Aaron Kennon has to say about all
Speaker 3: of this. Co founder and CEO at Clear Harbor Asset Management,
Speaker 3: they've got about one and a half billion in assets
Speaker 3: under management. Joining us once again from Stanford, Connecticut. Aaron,
Speaker 3: the story that we're all talking about deep seek, I
Speaker 3: am curious.
Speaker 7: I know, you know, we're trying to put it into context, trying.
Speaker 3: Because it's not like the whole market is selling off
Speaker 3: and everybody running for the exit door. So how do
Speaker 3: you think about something like this?
Speaker 8: Yeah, thanks for having me back, Carol. I think at
Speaker 8: the end of the day, we're seeing the evolution of
Speaker 8: artificial intelligence in large language models. We're seeing what I
Speaker 8: would call sort of the gradual commoditization of artificial intelligence,
Speaker 8: and you know, less compute power and you know, less
Speaker 8: GPU power, less electricity demand needed for a product that
Speaker 8: is ninety eight percent as good as the best product
Speaker 8: we have here in the United States is the story
Speaker 8: of the day. And obviously the hyperscalers are under a
Speaker 8: lot of pressure, as you mentioned at the break there
Speaker 8: in Videos down seventeen eighteen percent. Broadcom is down seventeen
Speaker 8: eighteen percent because they were the sort of hyped up
Speaker 8: companies so to speak, that we're going to be the
Speaker 8: beneficiaries of this AI demand. You have data center stocks
Speaker 8: which are very much part of that ecosystem down big today.
Speaker 8: You have sort of the cooling stocks that cool the
Speaker 8: data centers down big today. But then you have other
Speaker 8: parts of the technology landscape today that are interestingly doing
Speaker 8: quite well, and they seem to be almost like the
Speaker 8: beneficiaries of this commoditization of AI as I'm calling it,
Speaker 8: which is that which is to say, if you remember
Speaker 8: just a month or two or even a week ago,
Speaker 8: it was how much is you know, Facebook, how much
Speaker 8: are are Meta? How much are these other companies spending
Speaker 8: on cap x And essentially that's to purchase the hyperscalers,
Speaker 8: the Nvidia chips, the Broadcom chips. And now that narrative
Speaker 8: is changing. And so you have software companies like you know,
Speaker 8: Salesforce and work Day and Service now that are huge
Speaker 8: beneficiaries of the implementation of AI into their software packages.
Speaker 8: But now they're thinking this morning, well, I guess maybe
Speaker 8: this this will cost us less, and those stocks are
Speaker 8: in the green today.
Speaker 5: Yeah, that's that's interesting to hear. I'm wondering if you're
Speaker 5: using this as an opportunity to buy or sell. Are
Speaker 5: you changing asset allocation at all within your portfolios?
Speaker 8: Well, not doing a lot today, but happily it's challenged.
Speaker 8: If you're an active manager in Vidius fifteen percent of
Speaker 8: the Russell one thousand technology, you know if it's six
Speaker 8: percent of the S and P five hundred. So even
Speaker 8: if you're an active manager, and even if you own
Speaker 8: these names that aren't doing well today, you have to
Speaker 8: own more than within if your benchmarks the SMP, you
Speaker 8: have to own more than six percent of Nvidia and
Speaker 8: the SMP to say well, that's a real active bet, right,
Speaker 8: So unless you're underweighted, and so no, I we we
Speaker 8: feel reasonably good today. We have good broad diversification. I
Speaker 8: think there's been a lot of concentration in this market.
Speaker 8: We saw that in twenty twenty four, tim where if
Speaker 8: you look at the S and P five hundred, almost
Speaker 8: sixty five percent of the returns last year came from
Speaker 8: ten names, of which many are the names we're talking
Speaker 8: about right now. And you know to the extent that
Speaker 8: there's a broadening out of the market advancement in twenty
Speaker 8: twenty five, if we are up on the year, we
Speaker 8: welcome that. You look at the equal weight S and
Speaker 8: P five hundred today, it's only down one quarter of
Speaker 8: one percent today, quite telling, So.
Speaker 3: Forgive me, did you so? Would you are you buying?
Speaker 3: Would you be buying an end video? Would you buy
Speaker 3: a broadcom? Because they've all of a sudden been whacked
Speaker 3: in a big way. If you still believe in them
Speaker 3: fundamentally and I'm not sure if you do or I'm
Speaker 3: just curious.
Speaker 8: Yeah, we believe in growth opportunities within the technology segment.
Speaker 8: We would also argue that there has been a significant
Speaker 8: amount of passive dollars flooding into these names, driving them.
Speaker 8: If you look at the top seven names of the
Speaker 8: S and P five hundred, they're trading over thirty times
Speaker 8: forward multiples. You look at the bottom four under ninety
Speaker 8: three names trading at seventeen times. So do we think
Speaker 8: they're quality companies?
Speaker 10: Yes?
Speaker 8: Do we think that some of them are not trading
Speaker 8: at necessarily that the most attractive price point? Yes, and
Speaker 8: we think we can be in the affirmative on both.
Speaker 8: But we do think too that that doesn't necessarily mean
Speaker 8: over the long run that dollars are going to be
Speaker 8: accruing significantly away from these hyper scalers. But this broad
Speaker 8: opportunity across technology. Even the utility landscape today is quite interesting.
Speaker 8: Where this whole narrative around electricity demand, we've been hearing
Speaker 8: it for weeks and months. Look at Constellation Energy today,
Speaker 8: this is the deal.
Speaker 6: That Microsoft did right three Mile Island.
Speaker 8: That's down twenty percent today, yea.
Speaker 6: Down thirty percent today.
Speaker 8: Look at the water utilities today that no one wanted
Speaker 8: to talk about last year. They're up five six seven
Speaker 8: percent today. So it's really interesting. This rotation interesting?
Speaker 3: So interesting rotation? Is it an investible interesting rotation?
Speaker 8: Well, I mean, just look at multiples. I mean, are
Speaker 8: we gonna Are we going We haven't contracted permitted a
Speaker 8: nuclear build out since the nineteen seventies. The markets acting
Speaker 8: as though we're going to have a dozen nuclear buildouts
Speaker 8: contracted in twenty twenty five. It seems highly unlikely. I mean,
Speaker 8: we do think that we're gonna have less regulation. But
Speaker 8: even the announcement at the White House last week was
Speaker 8: quite quite interesting. Where you know, if you look at
Speaker 8: thee hundred billion dollars spend a year for four years,
Speaker 8: actually more than that, it's five hundred billion over four
Speaker 8: years that was announced to build out AI infrastructure. That
Speaker 8: timing looks a little off right now, but to build
Speaker 8: out AI infrastructure, the amount of electricity demand for those
Speaker 8: data centers would be about one point seven gig a
Speaker 8: lots per year based on the dollar spin that they're
Speaker 8: talking about. That's about that's that's over. That's about it.
Speaker 8: Actually it's two point seven excuse me, that's almost three
Speaker 8: nuclear power plants a year just for that project. So
Speaker 8: that we were getting I think over our skis in
Speaker 8: the marketplace to some extent a.
Speaker 10: Short time.
Speaker 5: Okay, if we're getting over ski if we were getting
Speaker 5: over skis now to continue the metaphor, where are we
Speaker 5: on the on the slope?
Speaker 8: Well, I think there are plenty of opportunities in the market,
Speaker 8: as I mentioned, if you look at forward multiples outside
Speaker 8: of this sort of you know, hyper focused area of technology.
Speaker 8: We've even in utilities as I mentioned, you know, the
Speaker 8: water utilities, they have nice roe growth, they're training at
Speaker 8: reasonable multiples. You look at the industrial segment of the market,
Speaker 8: we're seeing a lot of opportunity across the board there.
Speaker 8: If you look at you know, certain segments of the financials,
Speaker 8: we think MNA activity is going to accelerate this year.
Speaker 8: Private equity funds have in many cases reached the end
Speaker 8: of their life in terms of the limited partnership duration
Speaker 8: of ten years or more, and so we think that
Speaker 8: these companies are going to need to be either brought
Speaker 8: into the public market or sold in back into the
Speaker 8: private market this year. Huge opportunities for banks, advisory firms,
Speaker 8: companies that work on valuations of private equity. So you
Speaker 8: have plenty of opportunity there too.
Speaker 7: All right, Aaron, thanks so much.
Speaker 3: Aeron Kennon He is co founder and CEO Clear Harvard
Speaker 3: Asset Management, joining us from Stanford, Connecticut.
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