January 27, 2025 • 55 mins
Watch Carol and Tim LIVE every day on YouTube: http://bit.ly/3vTiACF.
Bloomberg Intelligence Senior Technology Analyst Mandeep Singh discusses Deepseek, a Chinese AI startup, that has demonstrated breakthrough AI models offering comparable performance to the world's best chatbots at a fraction of the cost. Bloomberg News US Semiconductor & Networking Reporter Ian King looks at the Deepseek impact on Nvidia. Bloomberg Businessweek Columnist Max Chafkin shares the details of his Businessweek story Musk Can’t Help Bringing His Rivalries to DC. Ian Wyatt, Senior VP and Director of Economics at Huntington Commercial Bank, provides a preview of this week’s Fed meeting and rate decision. Suzanne Dann, CEO, Americas at Wipro, talks about industries leading in AI adoption. And we Drive to the Close with Aaron Kennon, CEO at Clear Harbor Asset Management.
Hosts: Carol Massar and Tim Stenovec. Producer: Paul Brennan.
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Episode Transcript
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Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, radio news.
Speaker 2 (00:08):
This is Bloomberg business Week Insight from the reporters and
editors that bring you America's most trusted business magazine, plus
global business, finance and tech news. The Bloomberg Business Week
Podcast with Carol Masser and Tim Stenoveek on Bloomberg Radio.
Speaker 3 (00:27):
Our first guest, he's part of the family, Man Deep Sing.
He doesn't know, but we're not going to let him
go for sixty minutes because there's so much to talk about.
When it comes to Deep Seek, we want to get
into it. As you know, it's the Chinese artificial intelligence
startup Deep Seek, their latest model AI model, sparking a
one trillion dollar route in US and European technology stocks.
We have been seeing this AI shot play around the
(00:50):
globe on this Monday. A lot of questions though about
maybe valuations here in the United States, but what it
really means in the AI race. So let's get to it.
Man Deep is Bloomberg Intelligence Senior Tech industry unless Man
Deep seeing he's here in studio. You've been up early.
We've been listening to you, both Tim and I throughout
the day. Why is this all happening? Because for your world.
(01:13):
You guys, this has been on your radar, But why
is it all of a sudden on our radar and
why should we care or shouldn't we care?
Speaker 4 (01:19):
Well, every company has been talking about how capex needs
to go up because they believe in scaling laws. I
think what this development has shown is the hardware that
these companies have procured, they weren't using it efficiently and
literally it's both on the training side as well as
the inferencing of the models when it comes to using
(01:42):
it in chatbots and so on. And that's where I
think you have to ask yourself as an investor, are
you ready to pay up for these companies when they are,
you know, increasing their capex when we know they're not
running it efficiently. So I think a lot of questions
around just the efficiency of the hardware. I mean, the
scaling will continue just because there is more demand to
(02:03):
incorporate AI, but the fact that you know this model
does it so much more efficiently, I think raised a
lot of questions.
Speaker 5 (02:11):
Does it show that deep Sinck is actually ahead of
open AI, of Anthropic, of Lama at Facebook?
Speaker 4 (02:20):
No, In fact, they are using the output of open
AI and Anthropic and Lama to train their own models.
So think about this, Deep Sea. Didn't you know, train
this model from scratch the way open ai did. They
used output from open AI's models to train its own model.
(02:41):
So in effect, they are paying open ai, you know,
for all the API calls. But then they didn't have
to do things from scratch. And that's where you know,
if you are a meta Llama who has invested billions
of dollars in creating LAMA model, what was their incentive
to open source it to begin with? Because open sourcing
it made it easy for someone like deep Seek to
(03:02):
build their own model. And that's the thing about open sources,
you lose your IP. Someone else can come up with
a better approach to do things more efficiently, and suddenly
everyone runs to them.
Speaker 3 (03:14):
Man, Deep is this like the Apple Store. You don't
have to be first, you just have to be better.
Like I'm thinking about like creating a smartphone.
Speaker 4 (03:21):
I won't compare them to Apple yet, I mean, they'll
have their problem when it comes to distributing this model.
There's no way I can see, you know, Deep Seek
getting to the adoption of open Ai, especially here in
the US. But at the same time, you have to
give them credit for you know, just being novel in
terms of you know, the limited GPUs they had and
how they ended up using them.
Speaker 3 (03:42):
Do you trust the information, the research, and do you
trust that what they say they did they did do?
Speaker 4 (03:50):
Probably not. If they are saying six million dollars for
training their entire model, I don't trust it because when
I look at OpenAI costs for training their you know,
GPT four model, it was close to three hundred million.
Speaker 6 (04:03):
So we are talking about a fifty x gap.
Speaker 4 (04:06):
Now, even if Opening Eye wasn't very efficient, I don't
buy the fifty x gap. So clearly, you know there
is something that they are not counting when they you know,
release the paper. But at the same time, they've give
given us enough evidence to show that they are doing
things much more efficiently on the hardware side because of
the constraints they had Men Deep.
Speaker 5 (04:27):
I know you don't cover in video, and we're gonna
be speaking to Ian King in just a few minutes,
who's been covering in video in the ship space for years.
But we can't ignore that in videos down close to
eighteen percent right now. I mean it's shed almost a
fifth of its value in just today. Yes, the run
up over the last couple of years has been immense,
but a day like today is just mind boggling. I
think for a lot of people should in video in
(04:47):
your view be worried.
Speaker 4 (04:49):
I mean, look, that's where a lot of the questions
come is the cost for training the next model. So
if deepseek is saying that the cost was six million,
I think it should be really worried. But a lot
of people are apprehensive of that six million number because
they think it'll be higher. And it won't be three
hundred million the way open Aies was, but it will
(05:10):
be higher. And that's where I think open Ai or
Entropic will have a very tough time selling to their
investors that they need to build a one million GPU
cluster to train the next version of their model.
Speaker 7 (05:23):
Mandi, does this show that even though the US has been.
Speaker 3 (05:28):
Pretty rough in terms of restricting advanced technology, going over
to China, does this show that Chinese R and D
and Chinese companies can be pretty scrappy and pretty smart
and maybe figuring a go around and coming up with
their own way of competing against Nvidia.
Speaker 8 (05:42):
And the like.
Speaker 4 (05:43):
Yeah, and look, I think this could be another way
of them saying Look, we are open sourcing whatever we
have learned so far. So they want to build a
community because the export restrictions aren't going away, so they
are not going to get the you know, black ball
chips on paper and all the other allocation. And the
thing about model training is it's continuous. It's not a
one and done thing. So you have to continuously improve
(06:05):
your model. The other labs will go ahead if they
are not able to, you know, keep doing the training
and all the other stuff that other labs are doing.
So from that perspective, I think the whole aspect of
community building is front and center here. Yeah, but I
still think the cost parity is a very big concept here.
Speaker 5 (06:23):
Hey, before we let you go, Mandy, you do cover
meta platforms. The company out on Friday, Mark Zuckerberg saying
he was going to be spending more on Capex than
previously announced. Then the stock moved higher on Friday. Stock
was lower earlier in the session, but higher now. I mean,
I look at a move like that today and that
runs counterintuitive to kind of everything we're talking about.
Speaker 4 (06:43):
Look, there is a lot of confusion, but if there's
one thing that happened today is this moment is good
for open source, and meta Lama is an open source model,
so if anything into open source does get a nod
when it comes to you know what deep seek is
touting here.
Speaker 3 (07:00):
But you do also think about if it's cheaper for
companies to build out, then does everybody have to rely
on some of the bigger players.
Speaker 7 (07:07):
Maybe not.
Speaker 4 (07:07):
Next time Meta Lama will collect a fee from deep
seek for you know, using their model to train their
own models, so that could be a positive.
Speaker 3 (07:15):
I love this world that keeps us on our toes men,
deep saying keeps us on the straight and narrow. He's
Bloomberg Intelligence senior tech industry analyst here and has been
all over this story. We want to focus a little
bit more on semiconductors because we have seen that group
really taking a beating. You've got almost all thirty names
twenty eight out of thirty down in the Philadelphia Semiconductor
(07:36):
Index down about ten percent, the index as a whole.
Nvidios down seventeen percent. So ouch, what does this mean
for Nvidia specifically? We get to now Bloomberg News US
semiconductor and networking reporter Ian King. He's out there in
San Francisco. I don't know Ian, how we've all been
like talking about this non stop today you're the expert.
How are you thinking about Nvidia and possible impact the
(07:57):
reality of it all?
Speaker 7 (07:59):
How do you see it?
Speaker 9 (08:00):
I mean a lot depends upon how much reality there
actually is behind this claim behind you know, it was
a very well set out, well referenced research paper at
this point, and the model has been open sourced and
we'll see what people can do with it. The implication is,
of course that things got cheaper, things got more simple,
(08:23):
but we'll have to see that manifest itself in the
real world. And then obviously you can absolutely bet that
in video and a lot of other computer scientists that
some of the most powerful companies in the world are
looking at this right now working on this. For some
of them this would be great news. For others it
would be a disaster. So they'll be definitely testing out
(08:43):
the veracity of this, and I think the actual where
the truth lies will emerge with a bit more time.
Speaker 5 (08:50):
In What do you make of selloffs in other names
today Broadcom, for example, Marvel, I mean everybody is getting
hit in the sector. As Carol mentioned, twenty eight of
thirty names lower.
Speaker 9 (09:01):
I mean, yeah, yeah, the logic is absolutely clear, right,
I mean, if you are no longer a believer in
this exponential growth in spending, in this exponential need for
more and more computing, then you're going to sell Micron,
You're going to sell broad Coom, you're going to sell Marvel,
and of course you're going to sell in video or
(09:23):
you know. The logic based upon an assumption, and that's
what it is at this point is flawless. I mean,
for example, Broadcom, they are the key ingredient in terms
of these companies like Google that are now designing their
own chips for this type of purpose. So if there's
going to be less need for that kind of high
(09:43):
end chip, then it makes sense to sell them.
Speaker 3 (09:45):
I mean, none of this happens in a vacuum, right,
so I can only imagine the meetings that are happening
at Nvidia today and all of the chip companies. So
would you expect them to, you know, you know, tear
apart the research from this and try to understand exactly
what they did and then come back with their own response.
Speaker 9 (10:05):
You've got I mean, they've got to do that, right,
I mean, the the you know, if this was a
two or three percent move and a few market jitters.
Then you know you probably as a management team you
look into it fiercely, but you just keep your mouth shut.
Or we're just about to go into earning season, right,
So whether they like it or not, for example, Intel
on Thursday are trying to get into this market, They're
(10:26):
going to get asked about this.
Speaker 10 (10:28):
What have you got?
Speaker 9 (10:28):
How can you deal with this? Is this good for you?
These are all questions that I think, you know, everybody's
companies are going to be answering over the next two
or three weeks, and they better have some good answers.
Speaker 5 (10:39):
And do folks you taught you speak to who are
covering the industry, have they been waiting for a day
like today?
Speaker 10 (10:46):
Like was this bound to happen?
Speaker 9 (10:49):
I mean, you know, investors do two things right. You
have different types of investors, but basic pattern recognition is
supposed to be the skill that everybody can bring to this,
whether your technical or whether you're just a you know,
a general investor. So I think a lot of the
general investors will be like, let's let's not be on
(11:10):
the wrong side of what happened in two thousand with
all of the Internet sell off. Let's get out right now, right,
maybe we're at the peak. More sort of technically savvy
investors will probably take their time look at this and
try to find out just how much truths there is
there and just how many concrete implications there are.
Speaker 7 (11:28):
Well in terms of implications too.
Speaker 3 (11:30):
You know, a lot of what's been kicked around throughout
the day is you know, I feel like TikTok, you know,
version two point zero in other words, another Chinese company.
You know, you want to know how much the government
is involved and how much maybe you know, do they
support the r indeed, siphius from the United States, the
Committee on Foreign Investment in the United States, you know,
are they going to weigh in on this whether or
not you know, American companies or you know, can tap
(11:53):
into it. I mean, it's a whole other round of this,
it seems.
Speaker 11 (11:57):
Yeah.
Speaker 9 (11:58):
No, I clearly there's a lot of scrap rambling going on.
And you know, the path that's happened so far in
that particular area has been to restrict access to these
high end chips. So guess what, the country that is
restricted from these high end chips suddenly comes up with
the magic bullet solution, which says, maybe we don't need
as many of these high end chips, or maybe we
(12:19):
don't need them at all. So there is an element
of like, hmm, okay, is this really Is this the
answer that they want us to be concerned about, or
is this really the answer? Or have we given them
so much incentive to find a way around it that
they've poured all their energy into it being really smart
and got around it. I mean, layers upon layers of
(12:39):
things going on here, but in general, there are no
magic bullets in at least the chip industry. It tends
to be a pretty incremental industry where we see changes
over time. Software can be more volatile and you know,
is prone to more kind of instant changes in thinking.
But even then, and you know, the change to a
(13:01):
whole industry, the direction that's going in, it's a little
bit hard to imagine that one morning we all wake
up and go, oh dear right. But at the same time,
if you're an investor, you can't afford to ignore the possibility.
And if you're the CEO of in Video or the
board of InVideo or the senior management of video, you
cannot afford to ignore the possibility.
Speaker 5 (13:23):
Ian on a day like today, you know, we're certainly
focused on the big names that are moving lower by
double digits in video, certainly down Broadcom is lower today,
Oracles down by fourteen percent.
Speaker 10 (13:37):
But from a.
Speaker 5 (13:38):
Hardware perspective and from Deep six perspective, what do you
know about the hardware that Deep seek users to train
its own?
Speaker 9 (13:46):
That's no, and that's that's a very good question. That's
probably one that the US government are looking into, which is,
you know, some of the analysis that we've seen has
been like, look, yes, this model that they're citing that's
actually a derivative of another model. How did they train
that original model? So should we classify this derivative model
(14:07):
that they're offering up as part of this larger equation
which they must have developed with Western technology? And the answer,
simple answer is we do not know. And there's going
to be a lot of pressure on those that need
to know and should know to find that out. And
I think we're going to see a lot of reporting emerge.
(14:27):
We're going to see the government looking into this to
find out what did they have access to, should they
have had access to it, if what they had access
to was in fact more efficient computing than what say,
Microsoft is putting in place. Then wow, here we go. Right,
this is a breakthrough so many layers to this onion,
and that's not a very useful conclusion, but I think
(14:48):
it's the best that we can offer at this particular point.
Speaker 7 (14:51):
A lot of questions still out there. Ian, Thank you
so much, so appreciated. Of course.
Speaker 3 (14:54):
Our Bloomberg News US Semiconductor and Networking reporter.
Speaker 1 (15:00):
Is the Bloomberg Business Week Podcast. Listen live each weekday
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Speaker 3 (15:17):
It feels like the last week or so, topped off
by today's news on Deep Seek, has put the AI
story once again tim front and center in a super
big way.
Speaker 10 (15:25):
Yeah.
Speaker 5 (15:25):
Remember just last week, President Trump any group of tech
companies SoftBank, Oracle and open Ai initially planning to invest
one hundred billion dollars to build US based infrastructure, including
data centers for open Ai, the project we know called Stargate.
On that though, one very high profile tech and administration
voice who's not all in on it It's something that
Bloomberg BusinessWeek columnist Max Chaffkin gets into in his latest
(15:47):
story and in the latest Bloomberg BusinessWeek daily newsletter. You
can read Max's business Week story on the Bloomberg and
at Bloomberg dot com slash BusinessWeek. Max the co host
of the Lining podcast, also the author of the concheriont
Peter Tiel in Silicon Valley Pursuit of Power. Max, We're
gonna talk about elon Stargate in just a second, but
deep Seek is where I want to start because it's
(16:08):
what's hitting the tech names today. Well, I don't want
to say all tech names. It's what's hitting you know, Nvidia,
Broadcoms and of the other chip names in a big
way today.
Speaker 12 (16:16):
How are you looking at absolutely well, you know, as
you're hinting at with this discussion of stargate, until basically
this weekend, you know, AI infrastructure was seen as.
Speaker 6 (16:25):
The end all be all.
Speaker 12 (16:25):
You know, they were talking about not not one hundred billion,
five hundred billion, right and at times Sam Altman has
said he's gonna he's gonna need seven trillion dollars in
you know, funding for AI infrastructure, and there's been this
sense especially among Google, Open Eye, a bunch of these
big players, that this is gonna be the thing that
(16:46):
like only hyperscalers are going to be able to compete
in that whoever has the most infrastructure, even whoever has
the most power. Right, We've seen a big run up
in nuclear stocks and things like that, so so, and
this sort of threw all that out the window because
if we're to believe what deep seek is saying, this
was done with a much much lighter weight, uh you know,
amount of usage of chips and it and it actually
(17:08):
is running a lot more efficiently efficiently. So that suggests,
right that that these this crazy run up we've seen
in demand for GPUs and so on might be overheated.
And we we had other reasons to think that there
was perhaps some sort of bubble or a little bit
of frothiness in this market. And and I do think
if it hadn't been this, it might have been something else.
Speaker 10 (17:28):
Right.
Speaker 6 (17:28):
I think investors were and are primed.
Speaker 12 (17:31):
To see, you know, to see to see potential flaws
and with the with the business model that so many
have bought into.
Speaker 3 (17:38):
So not necessarily an end of like the AI spend,
but just kind of a twist and turn in the story.
And there's still more to be known, right Max, in
terms of the reliability of the information we're hearing from
them and the reality of it.
Speaker 12 (17:49):
Yeah, there's so much we don't know here, and again
it's definitely worth I think approaching Deep Seek's claims skeptically
and also understanding that there if they were able to
develop a much more inexpensive model that could help parts
of the AI market. It doesn't necessarily mean that all
of this goes away or something, but it may.
Speaker 7 (18:10):
Make it more accessible, right, that's less expensive.
Speaker 12 (18:12):
Yeah, it definitely, but it could cause investors to like
dramatically revalue like some of their assumptions.
Speaker 5 (18:18):
How does it change the narrative around what China is
able to do when it comes to AI right now
and sort of the tech race that's happening there. The
thing is, if they weren't supposed you know, there are
these chips, A lot of these chips are not supposed
to go to certain parts of the world.
Speaker 12 (18:30):
Right, So that so there's something potentially troubling there. If
you're if you're looking at the attempts to restrict certain
US technology to China, it seems like either those restrictions
aren't working that well, maybe some GPUs found their way
to China, or or that the Chinese software industry has
found ways around it, which would also be potentially problematic,
(18:54):
I suppose from a sort of US national security perspective,
at least from the point of view of the China
Hawks who have been sort of warning about this, and
that includes many of the Silicon Valley companies like remember,
one of the big reasons to justify this, like massive
spend on AI And one of the reasons that many
of these folks, including Sam Altman, sees this as a
(19:15):
thing that government should be involved in, is because they
have been arguing that without this, without spending huge sums
of money on say on power or investing in infrastructure
in terms of data centers, that we would fall behind
behind the Chinese tech startups. And that may you know,
if you sort of extrapolate from this very small piece
of news, you might say, Okay, well it's happening anyway.
(19:37):
So that sort of throws everything into a bit of disarray.
Speaker 7 (19:40):
All right, So let's get to stargate. Love the name,
love the name Elon Musk. I find it interesting. I
think we all found it interesting.
Speaker 3 (19:48):
That here's this big announcement right that comes out of
the Trump administration last week, and Elon not so in
on it?
Speaker 6 (19:55):
Is he no, not in on it at all.
Speaker 12 (19:57):
You know, it wouldn't be surprising if if you had
this big announcement with Donald Trump and the CEOs of
some major companies talking about huge numbers, right they were saying,
we're going to invest one hundred billion dollars immediately five
hundred billion with the next four years, would not have
been surprising if some people said this sounds like a
political stunt, I'll believe it when I see it. It's
(20:17):
what made this thing that happened last week so surprising
is that the person saying that was a senior advisor
to Donald Trump, and it was Elon Musk.
Speaker 6 (20:26):
Tweeting over and over and over again last week.
Speaker 12 (20:29):
I mean, the last time I checked, twenty times, he's
tweeted a few more times. You know, the usual mix
of i'd say, off color jokes and put downs. You know,
he's called Sam Altman, who was of course on stage
with Donald Trump, a swindler. He suggested the announcement was fake,
and Trump has sort of responded by saying, hey, you
know Elon Musk has a dispute with one of the
(20:50):
people in this in this deal, which is true.
Speaker 6 (20:54):
Sam Altman and Elon Musk have.
Speaker 12 (20:56):
Been feuding more or less in public for the last
couple of years, So we're sort of seeing I'd say,
you know, maybe one of the downsides to having somebody
who is as deep in the business world also involved
as a advisor to the president.
Speaker 5 (21:10):
I mean, is Elon Musk at this point saying, Hey,
I gave you some giant bags of money to help
you win the election.
Speaker 7 (21:15):
What were you thinking?
Speaker 5 (21:16):
And now you're doing this? Does this risk driving a
wedge between the two of them?
Speaker 6 (21:20):
I think for both Musk and Trump.
Speaker 12 (21:23):
I mean, there has been over the last couple of
months people who have been hot on high alert for
signs that this relationship might be might be breaking up.
And I would say that it doesn't seem like this
has done it either. You know, you know, Trump has
cracked jokes before, We've seen these tweets. There have been
there was a dispute over the H one B visa
thing both Musk.
Speaker 5 (21:43):
And maybe that led to the divorce between Ramaswamy and Musk.
Speaker 12 (21:46):
Yeah, yeah, at least according to some reports. You know,
it's possible there are other reasons as well. But but
what I'll say is it seems like Musk and Trump
are still working closely together. I'd say Trump's comments about
this to me suggested that he was untroubled by Musks,
you know, apparently kind of trying to undermine or or
undermine some of his partners in this deal. And I'd
(22:07):
say part of that is that, you know, there's not
necessarily government money going into this. In the Stargate thing,
it really was basically a media event for Donald Trump
to announce a big business deal so that he can
claim credit for, you know, helping to spur the economy.
It's kind of like a vibes thing. And I think
because of that, I'm not sure it really hurts Trump
(22:29):
all that much to see Elon Musk dissing Sam Altman
on Twitter.
Speaker 3 (22:33):
Well, you write in your story, Max, you said Musk
has always treated his conflicts of interest like features rather
than bugs, seeming to run his normally independent companies with
their nominally independent shareholder basis as if they were a
single conglomerate. You talk about employees being lent out, sharing
of resources and stuff.
Speaker 7 (22:49):
So conflict he's kind of all in on this too.
Speaker 12 (22:52):
Well, yeah, absolutely, this is a big part of First
of all, competing in this area is a big part.
Speaker 6 (22:59):
Of Elon Musk's big plan for.
Speaker 12 (23:01):
His companies, not just Tesla, which of course is developing
you know, advanced robotics and is trying to build self
driving cars, but also x Ai, his his chatbot competitor,
so he is very much playing in this market. He
is also competing to buy these Nvidia these high end
in Nvidia GPUs. He's building giant data centers, so he
(23:23):
very much has a dog in this fight, and that's
why he's doing this. And I think Trump's attitude seems
to be that's all out in the open, as long
as people understand that what's behind this is a business dispute.
Speaker 6 (23:36):
Again, he said, well, one of the things is.
Speaker 12 (23:38):
Is he hates one of the guys in the deal,
an obvious reference to Elon Sewings and but then Trump said,
you know, I hate people too.
Speaker 7 (23:47):
So we all have a problem.
Speaker 11 (23:49):
Child.
Speaker 5 (23:50):
I wonder you know what what Donald Trump has been
able to do in recent months has been pretty incredible
when it comes to the tech industry. I mean a
week ago, Carol and I were sitting here looking at
the stage and during the inauguration, and you saw titans
of industry who were not at previous inaugurations there all
collectively getting behind the president. I mean, he's he is
this larger than life figure who perhaps can bring people
(24:11):
together who don't like each other, maybe because he offers
them something that they want.
Speaker 12 (24:18):
Yeah, well, Trump probably more so, at least than than
foreign President. Biden approaches the presidency in a way that
I think would be fair to describe as a little
bit more transactional.
Speaker 11 (24:27):
Right.
Speaker 12 (24:28):
He's willing to bend his policies to make deals. It's
the whole thing that he's about, and in certain ways,
right that works well for CEOs.
Speaker 6 (24:37):
I also think there's a lot going on there.
Speaker 12 (24:39):
There was a lot of built up anger in Silicon
Valley over some of Biden's policies over anti trust for instance,
and you have a lot of opportunism right now. There's
a sense that they have leverage because by showing up
in these Trump things, they they're giving Trump some additional
credibility and they're trying to use that to get you know,
what they can, which is, you know, favorable policies, favorable
(25:01):
and trust policy.
Speaker 7 (25:02):
We're going to talk about that in the next couple
of hours.
Speaker 5 (25:05):
Hey Max, do you want to go back to where
we started and deep Seek because we're getting some breaking
news and video is out saying that deep seek is
quote excellent AI advancement and says that deep Seek's work
quote fully export control compliant and says that inference requires
significant numbers of its GPUs. This is an email statement
on the deep seek AI model. They're they're coming out
(25:27):
and saying talking about it. I'm wondering how you view that.
Speaker 12 (25:30):
I mean, I think it's first of all, everybody's talking
about it. It seems like it seems like they that
they have to and they also I think in that
statement and I haven't looked at I'm just hearing it now,
it seems like an attempt to address suggestions that perhaps
deep seat Seek had access to you know, improper access
to GPUs or something like that.
Speaker 6 (25:49):
It sounds like they are saying, no, that's not the case.
Speaker 12 (25:52):
Again, it definitely seems like this would be a business
challenge for for Nvidio if you were if you were.
Speaker 6 (25:58):
Able to do the kinds of hatbot.
Speaker 12 (26:00):
You know, work much much more efficiently with about the
same sort of level of quality that's gonna make these
GPUs perhaps not as valuable.
Speaker 6 (26:11):
But again a lot. There's a lot here that we
don't know.
Speaker 12 (26:14):
And you also have seen people on the other side
of this saying, actually, this is going to be great
because it's gonna make these chatbots so much cheaper. We're
gonna see tons of them. Essentially, we're gonna make it
up on volume. It's hard to know how to evaluate that,
and we don't know that much about how this was
put together or really just how good the quality looks.
People have been playing with it only for a short amount.
Speaker 3 (26:35):
Wait you want details. Excilly you great stuff, Max, Thank
you so much. Bloomberg Business Week commnist Max Chafkin is
also co host of the Elon Inc.
Speaker 7 (26:44):
Podcast.
Speaker 13 (26:44):
You could check that out.
Speaker 3 (26:45):
It's on the Bloomberg and also at Bloomberg dot com
slash Elon Inc. Max is also author of the contrarian
Peter Teel and Silicon Values Pursuit of Power.
Speaker 2 (26:56):
This is the Bloomberg Business Week podcast. Listen live each
week day starting at two pm Eastern on applecar Play
and Android Auto with the Bloomberg Business app. You can
also listen live on Amazon Alexa from our flagship New
York station. Just say Alexa played Bloomberg eleven thirty.
Speaker 3 (27:13):
Hey, I guess say reading in this morning, Morgan Stanley
continues to recommend that investors hold long five year treasuries
ahead of two potentially devish market catalysts. And those catalysts
are the January FED meeting, So not this week's meeting
and then this month's job report. Meantime, you've got jp
Morgan stay staying along the front end of the treasury
curve well Bimo positioning for two quarter point FED cuts
(27:36):
this year. So while we are focused so much tim
on tech and AI news this morning, let's not forget
we at the first FED decision of twenty twenty five,
That decision out on Wednesday.
Speaker 10 (27:44):
Okay, with more on that, With.
Speaker 6 (27:46):
More on that.
Speaker 5 (27:46):
In the studio, we got Ian Wyatt's senior vice president
director of Economics at Huntington Commercial Bank. It's a division
of the publicly held roughly twenty five billion dollar market
cap Huntington Bank. Shares Ian, good to see you. Look
before we jump been to exactly what we're going to
hear from Fed sho Jpowell, I would imagine he might
get some questions around AI and the market sell off
(28:07):
this week. Whether or not he answers those questions, that
certainly remains to be seen. I would figure out a
way to ask him a question around that, How do
you think, how are you looking at what's happening in
the market this week, especially ahead of this FED meeting?
Speaker 14 (28:20):
I think, well, first, I think in terms of the
FED meeting, not related to AI, I think long our
view is that there's still inflationary pressures out there in
the economy when I taught, but I think it's really
we have this two speed labor market we're seeing. We're
seeing is for lower end jobs. You know, where's the
job growth been. It's been restaurants, it's been hotels, It's
(28:41):
been a lot of service areas. And when I talk
to companies in those areas, whether you're manufacturing, transportation, still
a tight labor market. They're having a hard time finding workers.
If you're talking about more of a college job, professional
and business services, where are we not getting job growth?
Speaker 10 (28:55):
It obviously has been down.
Speaker 14 (28:56):
We've seen you know, them focusing on cash flow more
than job growth. So we kind of have this this
two speed labor market where you still have a tight
lower end, and the problem for inflation is a lot
of those industries are very labor intensive.
Speaker 10 (29:10):
You know, childcare for example.
Speaker 14 (29:12):
It's something where labor or restaurants, labor makes up a
huge percentage of your cost structure, and they're still feeling that pressure.
So I think we've probably been on the low end
of the FED saying in terms of cuts for twelve
months now. Yeah, now I think we're more in line
with the two cuts roughly this year. But I still
think that pause holds for a while because I think
(29:34):
there is that fundamental underlying inflationary pressure that is not
really when you tease out inflation, you look category by category.
Speaker 10 (29:43):
It's not been durable goods.
Speaker 14 (29:45):
Durable goods have been coming down, but it's also stuff
that consumers can choose not to buy.
Speaker 3 (29:49):
So I just want to stay with AII for a moment.
That AI spend the economic you know, activity, it may
impact on the upper down side. You know, how does it,
if at all, factor into any of your ex economic
models when it comes to growth, when it comes to inflation,
and then ultimately to FED policy.
Speaker 14 (30:04):
You know, AI caused me to get one call really
wrong last year. It was I thought construction employment was
going to come down. Yeah, I thought, you know, multifamilies
coming down. We saw warehouse space is over supplied. Now
obviously office has its issues, and I underestimated how much
it would be chipsacked.
Speaker 10 (30:20):
It would be the.
Speaker 14 (30:21):
Chip plants like Columbus for example, or we're headquartered. They
have that massive intel plant, a couple of the largest
cranes in the world operating there. And AI was a
huge part of this. And I still think there's this
huge first mover advantage. You don't want to be the
last company. You want to be the last company that
still gets a power connection versus the first where they
(30:41):
say no, we don't have enough juice, we can't afford
or we can't build, you know, connect you for five years.
Speaker 10 (30:48):
And I think that that case still remains.
Speaker 6 (30:51):
Yeah.
Speaker 14 (30:51):
I also think there's another bullish case for power that
when you look at the forecasts and really baked invert.
Speaker 10 (30:56):
What is that about? Transportation?
Speaker 14 (30:58):
So so, okay, if you look at US energy consumption,
roughly fifteen percent of US energy consumptions residential, that's what
we always think of our power. Thirty seven percent of
US energy consumption is transportation. Right now, over the last
six months roughly ten percent of US car sales we're
up to have been plug in vehicles now. Vehicle fleet
takes a long time to turn over in the US
(31:19):
average vehicle ages over twelve years now, it takes a while.
But as that starts to kick in, if EVE even
got a small fraction of that thirty seven percent shifting
from fossil fuels to electric power, it doesn't really matter.
Speaker 10 (31:33):
The source, whether it's gas or solar.
Speaker 14 (31:35):
Or whatever, you have a very different outlook for electric
demand at the US. And I think that also means
utilities are going to have to build a ton of infrastructure.
Speaker 5 (31:44):
Does that get derailed by the Trump administration pushing back
against EB subsidies and moving trying to get people to
move away from evs.
Speaker 14 (31:51):
I mean, I think it slows it to some degree.
I think that's definitely. You know, you're seeing a shift
administration policy. If you look at Germany, for example, when
they cut their TV subsidies, that dramatically slowed EV's sales.
But it's still something where there's a lot of the
global market is shifting in that direction. Autos are shifting
that way.
Speaker 7 (32:11):
China's all in, China's all in.
Speaker 14 (32:14):
I mean, you talked to a friend of mine runs
FedEx distribution, owns a couple of Fredecks distribution places, and
he talks about, you know, the gas prices on his
delivery trucks, and he's really looking, how do I lower
my fuel expenses? And that's really a perfect application for
EV short range so stop start driving?
Speaker 10 (32:32):
So does he do that with Rivians?
Speaker 14 (32:34):
Like yeah, I mean he's looking at Yeah, he's looking
I mean, Rivian's just starting to sell beyond Amazon now,
they're just moving beyond Amazon or filling those initial orders,
whether it's that or Forward and Stillantis both have products
in that market as well.
Speaker 10 (32:50):
Sorry here, I know we're supposed to be talking about.
Speaker 3 (32:51):
The I kind of love this because it's a fuller
picture of kind of the markets and really our economy.
So having said that, I mean, I don't know this
January meeting, the decision on Wednesday Ian, is it kind
of a snoozer because we don't really expect anything? Or
is there a fine noodle, a noodle, a fine needle
that j Powell has to thread here?
Speaker 14 (33:11):
In some ways I think thematically we've seen you know,
a year ago when he did the Palll pivot, you
felt like there was pushback right after he spoke at
that presser, and it definitely seemed like he was on
the duvish end of the spectrum. If you look back
at the September vote on the dot plot, you can
see almost half of Fed Governor's only wanted three cuts
this fall. So that would mean essentially there should have
(33:33):
been one twenty five in each meeting, and that meant
they were opposed to fifty in September. Now, obviously they
all get in board, they all push in the same direction,
but if you look at the minutes, you look at
the notes, I think he's still again. I think this
is a repeat of about a year ago. It's he's
on the dubvish end of the spectrum. He has to
get the board to come along with him. And I
(33:53):
don't think I think. I think the inflationary pressure is
still there. I still think there's some underlying and when
I talk to companies in the economy, depending on the
part of the labor market they're in.
Speaker 10 (34:05):
It's still there.
Speaker 14 (34:06):
It's it's still significant, and I think that helps some
of the more hawkish voices on the FED, where the
very narrowly balanced FED I think on this.
Speaker 3 (34:15):
So it's really labor costs that you're most concerned about.
It's not the price of eggs that everybody keeps talking about.
It's really labor costs.
Speaker 14 (34:23):
Well, yeah, I mean, I'm the grocery shopper in the family,
so I definitely noticed the price of eggs. And I
know used to work in Georgia, so I know, you know,
top egg economy, top egg producing state in the country
is basically offline right now because of bird flu. So
there's some big things going on there. But now I'm
much more concerned about rent growth. I mean, that's a
good sign we're seeing on the inflationary front. If you
(34:43):
look at the market based rent indexes, you can see
you're at one one and a half percent. The problem is,
you know, two thirds of Americans on their home A
lot of that single family we're still seeing and the
implicit rent deflator from that comes from rents on single family,
not multi family, and that's still feeling pressure.
Speaker 7 (35:01):
What did you want to say, I know I jumped in.
Speaker 5 (35:03):
Oh, I just I wanted to just say in videos
down eighteen percent, everybody, that's the that's the day. Looking
at Broadcoms down eighteen percent, Oracles down seventeen.
Speaker 7 (35:13):
Percent, but no inflation there.
Speaker 10 (35:16):
Then that's a backdrop of some would say.
Speaker 3 (35:18):
It's on sale or maybe not, depending on the outlook.
This was really fun. Come back soon and why are
senior vice president and director of economics loved where the
economic conversation went over at Huntington Commercial Bank.
Speaker 7 (35:29):
Joining us here Tim in studio.
Speaker 1 (35:31):
You're listening to the Bloomberg Business Week podcast. Catch us
live weekday afternoons from two to five y's during Listen
on Applecarplay and Android Auto with the Bloomberg Business app,
or watch us live on YouTube.
Speaker 5 (35:45):
Susy dan Is Cudy of America's over at Wi Bro.
It's a global consulting firm that provides services related to
IT cloud and yes AI. And that's really what we
want to talk to her about because that is why
we're seeing the selloff concern that a cheaper AI model
from the Chinese startup Seek could make valuations of these
tech that has powered the bull market pretty tough to justify.
It's what we spoke to Gena Martin Adams about just
(36:07):
a minute ago. Suzanne joins us from East Brunswick, New Jersey. Susanne,
you are just back from Davos, where we know AI
was front and center. Given comments that we areed from
Alexander Wong, who is the founder at CEO over at
Scale AI, how would you though characterize the AI conversation
that was happening over at Davos.
Speaker 11 (36:26):
Well, thank you both for having me. Everything was AI
last week. You could walk down the street and every
storefront had something about AI or was talking about AI.
Speaker 13 (36:36):
So it was front and center.
Speaker 11 (36:38):
This is clearly a defining year for AI and for
jen AI, and businesses are looking to figure out how
do they drive value from this. Most CEOs believe that
it's going to significantly change the way they do business
in terms of how they create and deliver value and
obtain value from the work that they do. And there
(37:01):
was a clear momentum around, you know, defining the strategy
in which they're going to invest in AI to create
that value.
Speaker 3 (37:08):
Why do you think it's that they were saying or
why is it that this is going to be a
defining year, especially on a day when we kind of
just got you know, a company that might say, hey,
you don't need to do the big span or you know,
we can do it. It's a different maybe financial model
in terms of the buildout, I feel like we're still
kind of finding our way. So why why is it
(37:30):
that twenty twenty five is the defining way. I'm not
quite sure how to read that.
Speaker 13 (37:33):
Well.
Speaker 11 (37:34):
I think last year everybody was talking about AI and
just piloting with genai. It was, you know, it became
it's democratized. Everybody has access to it, we can use it.
I think the GENAI races and during a new phase.
We saw it this morning and I think we're still
in the beginning, you know. To me, it really calls
to everyone that this emphasizes the pace we're going to
(37:55):
see innovation and really figuring out how we can create
agile and environments to deliver on AI. And at the
end of the day, it's going to be about the
quality of the data that these AI are trained on
and deliver for our clients to really deliver value to
the organizations, regardless of how much they spend. And I
think you know where we see it is our clients
(38:16):
really are talking about the data they need to fuel AI,
whether it's a large language model or a small one.
Speaker 5 (38:22):
I'm just just for context, because we do speak to
a lot of folks who run consulting firms or run
parts of consulting firms. Just give us an idea of
your clients, the type of clients you have, and you
know who's out there working with you.
Speaker 13 (38:34):
Yeah, so I work, so my responsibility.
Speaker 11 (38:35):
I have clients across financial services, oil and gas, energy
and utilities, high tech, and manufacturing and automotive. So I
have clients across many different industries and many different challenges
that can be solved with them without AI.
Speaker 5 (38:49):
So who would you say is leveraging AI the best
right now?
Speaker 11 (38:52):
Well, you know, AI is a proven and it's been
around for ten years. We've been using in AI, and
many of our financial service as clients have been using
AI and machine learning models for years. It's only now
with GENAI we're seeing this acceleration and that's what's truly
exciting is how we can leverage the genai applications. You know,
we've been also leveraging it internally so that we can
(39:15):
learn and then deliver those learnings to our clients. We're
leveraging in HR, we're leveraging it illegal across the board
to make sure that we understand how AI can be
used and understand the foundation and the governance and responsible
nature in which we need to deploy it and train
our people to make sure that it's successful.
Speaker 3 (39:35):
So, Susan, what I'm wondering is like on a daylight today,
where this story a company that nobody had really are
I should say nobody because our Bloomberg intelligence teams like, yeah,
our team overseas has been writing about deep Seek for
you know, the last couple of years, so it's not
necessarily new to them, but certainly new to I feel
like our conversations when it comes to AI in general.
Speaker 7 (39:55):
So I am.
Speaker 3 (39:55):
Curious, have you guys your team, you know your phone's
been ringing today's say, wait, what is this deep Seek?
And you know I've been spending X on my AI
infrastructure build or you know, making plans? Do I need
to rethink it? Do I not need to spend as much,
you know, on site versus not? You know what tell
us about today and the conversations perhaps that you guys
(40:18):
have all been having.
Speaker 11 (40:20):
So today it's all over the news. It's absolutely correct,
everyone's talking about it. I think the reality is over
time there's going to be winners and losers. You know,
the role that we play is helping our clients make
sure they have the foundations in place. One of the biggest,
and I'll go back to it, is the data.
Speaker 13 (40:36):
And the people.
Speaker 11 (40:37):
You know, training your teams to think about AI first
and how to bring AI into a business to add value,
so it could make an AGENC that could do make
autonomous decisions and be managed appropriately. The data foundations, so
the models don't hallucinate. All that has to be done
regardless of the technology that you choose. So that's where
(40:57):
I think the real area that we can add value
in helping our clients navigate both the frameworks, the governance,
the training of the people, all the change management, and
the data.
Speaker 13 (41:07):
All that still has to happen regardless.
Speaker 11 (41:09):
Of which model that you choose to use and the
foundations you build on.
Speaker 7 (41:13):
So the spend is going to still happen. Nobody's going
to put back.
Speaker 11 (41:17):
Yeah, I think it'll depend on what the use cases
and what the spend will be. So I think that
is yet to be determined, depending on the models that
our clients use. And many of our clients are using
large models, and many of our clients are using their
data and developing small models. But you know, I do
think this is a race that is continuing and we're
going to see this evolution and many more to come.
Speaker 5 (41:38):
Where do you see the actual money savings happening with
these companies that you work with? Is it from a
customer service perspective? The whole rise of the AI agent?
Where do companies where would our margins be helped?
Speaker 13 (41:54):
Yeah? So I think there's two things.
Speaker 11 (41:55):
You know, there's a whole site of productivity and efficiency.
Seeing that in development, you know, making our developers more
productive and more efficient, and we're seeing it in testing
of technology and applications. Absolutely, we're seeing that today. There's
also things like contact center where we're helping clients in
servicing and using AI to make the agent smarter and
(42:18):
delivering higher quality engagement. So there's lots of area where
we're seeing productivity and efficiency and the question is does
that translate into our clients being able to add more
higher value work to those or driving the costs down
in their business.
Speaker 13 (42:31):
And we're seeing both. You know, we launched just as I.
Speaker 11 (42:36):
You know, one example is whippro now, which is a
HR intelligent agent and we've put all of our HR
policies and procedures into this agent and it's serviced over
eight million queries to date at greater than ninety percent accuracy.
We've been able to reduce the number of of HR
employees to service those queries and to service those and
(42:59):
be able to reap purpose. So you can say that's
a great efficiency play, but it's also a great employee experience.
Our employees are able to get real time information, real
time insights into HR and be able to have a
better experience than maybe looking for documents in lots of
flou volders.
Speaker 3 (43:16):
Well, that's what I wanted to ask you. What was
the kind of satisfaction rate as I play around or
increasingly am you know, working with chats chatbots to deal
with service customer service issues. I mean, sometimes it's really
great and sometimes it's not. So I'm curious from your
internal team how did it go or what you guys
have learned in the process, because it's never perfect right
out of the gate.
Speaker 13 (43:36):
No, it isn't, and it takes time.
Speaker 11 (43:38):
In the early days, you know, the the the quality
wasn't as good as it is today, and the satisfaction
is really high. I don't have the specific numbers. I
know I've used it and it has been great. The
reality is it's not the chat bots, which is based
on rules. It's the it's an intelligence agent, so it
learns over time and we all know.
Speaker 13 (43:58):
That's the power of AI. AM that's what it a
great experience.
Speaker 11 (44:01):
So when something needs to be adjusted, it can be
and when there's feedback, it constantly is iterating, so it's
only getting better over time and becoming that that, you know,
the most intelligent HR agent it can be. So I
think overall it's the right direction in terms of creating
a great employee experience and enabling HR to do what
(44:21):
they should be doing and taking care of people and
not just answering simple questions. And I think that makes
it for a more interesting HR experience for that employee
as well.
Speaker 5 (44:31):
What about the administration and the role of the Trump
administration in this. We started the announcement of Stargate last week,
one hundred billion up to five hundred billion dollars of
investment from AI companies. What was the conversation happening around
this administration with regard to AI.
Speaker 13 (44:46):
I'll tell you.
Speaker 11 (44:47):
At Davos, there was optimism around the global economy and
the resilience as well as the US economy, and overall,
there was interest around what we're doing around AI as
well as regulatory policies, and I think overall there was
really just great optimism in Davos around the US economy.
Speaker 3 (45:08):
So in terms of kind of where we go from here,
you know you're in it. You guys are doing it
at your own company, you're working with companies consulting when
it comes to AI. You know this is your number
three right that this continues certainly to be an investment theme,
although taking a big hit in today's session, no doubt
about it. So top of mind that you think investors
(45:28):
should be watching out for. And just got about thirty
forty seconds here.
Speaker 11 (45:32):
Yeah, I see the investment in AI to continue and
I and you know, I think the speculations is going
to double in the next couple of years.
Speaker 13 (45:41):
I don't believe that test changed.
Speaker 11 (45:44):
Our clients are investing A and AI, and I think
today's announcements and what we saw today only emphasizes the
importance of.
Speaker 13 (45:53):
The innovation moving at pace.
Speaker 11 (45:55):
And I really do believe it shows that those who
invest now in bringing AI into and learning and experimenting
and scaling will be the market leaders. It's going to
disrupt every industry and that's what We're encouraging our clients
to do to lean in and you know, power their
organizations with AI. And that's why we've added you know,
(46:16):
whip Pro powered AI and we really believe us being
powered by AI will only help our clients be successful
and implementing in their own business.
Speaker 5 (46:24):
Susan Dad, CEO of America's over at the global consulting
firm whip Ro, joining us from New Jersey this afternoon.
Speaker 7 (46:35):
Macout you let me drive.
Speaker 12 (46:37):
Oh no, no, no, no, this is not a toy, Judge, Honey, please.
Speaker 11 (46:42):
I.
Speaker 3 (46:45):
Want to drive.
Speaker 4 (46:48):
It's a good question.
Speaker 2 (46:53):
This is the drive to the clothes that plungs for MEFIC.
Speaker 3 (46:58):
On Bloomberg Radio, all right, everybody got about eighteen minutes
left to end the Monday trade. You are listening and
watching Bloomberg Business with Carol Master along with Tim Stenovek
live here in our Bloomberg Interactive Broker studio. You heard
Charlie and Bill Maloney breaking it down. S ANDP down
about one point seven percent, the Nawstak one hundred down
the most when it comes to the index trade looking
about three point two percent decline here. I am curious
(47:21):
to see what Aaron Kennon has to say about all
of this. Co founder and CEO at Clear Harbor Asset Management,
they've got about one and a half billion in assets
under management. Joining us once again from Stanford, Connecticut. Aaron,
the story that we're all talking about deep seek, I
am curious.
Speaker 7 (47:37):
I know, you know, we're trying to put it into context, trying.
Speaker 3 (47:42):
Because it's not like the whole market is selling off
and everybody running for the exit door. So how do
you think about something like this?
Speaker 8 (47:50):
Yeah, thanks for having me back, Carol. I think at
the end of the day, we're seeing the evolution of
artificial intelligence in large language models. We're seeing what I
would call sort of the gradual commoditization of artificial intelligence,
and you know, less compute power and you know, less
GPU power, less electricity demand needed for a product that
(48:15):
is ninety eight percent as good as the best product
we have here in the United States is the story
of the day. And obviously the hyperscalers are under a
lot of pressure, as you mentioned at the break there
in Videos down seventeen eighteen percent. Broadcom is down seventeen
eighteen percent because they were the sort of hyped up
companies so to speak, that we're going to be the
(48:38):
beneficiaries of this AI demand. You have data center stocks
which are very much part of that ecosystem down big today.
You have sort of the cooling stocks that cool the
data centers down big today. But then you have other
parts of the technology landscape today that are interestingly doing
quite well, and they seem to be almost like the
beneficiaries of this commoditization of AI as I'm calling it,
(49:00):
which is that which is to say, if you remember
just a month or two or even a week ago,
it was how much is you know, Facebook, how much
are are Meta? How much are these other companies spending
on cap x And essentially that's to purchase the hyperscalers,
the Nvidia chips, the Broadcom chips. And now that narrative
is changing. And so you have software companies like you know,
(49:23):
Salesforce and work Day and Service now that are huge
beneficiaries of the implementation of AI into their software packages.
But now they're thinking this morning, well, I guess maybe
this this will cost us less, and those stocks are
in the green today.
Speaker 5 (49:38):
Yeah, that's that's interesting to hear. I'm wondering if you're
using this as an opportunity to buy or sell. Are
you changing asset allocation at all within your portfolios?
Speaker 8 (49:49):
Well, not doing a lot today, but happily it's challenged.
If you're an active manager in Vidius fifteen percent of
the Russell one thousand technology, you know if it's six
percent of the S and P five hundred. So even
if you're an active manager, and even if you own
these names that aren't doing well today, you have to
(50:10):
own more than within if your benchmarks the SMP, you
have to own more than six percent of Nvidia and
the SMP to say well, that's a real active bet, right,
So unless you're underweighted, and so no, I we we
feel reasonably good today. We have good broad diversification. I
think there's been a lot of concentration in this market.
(50:30):
We saw that in twenty twenty four, tim where if
you look at the S and P five hundred, almost
sixty five percent of the returns last year came from
ten names, of which many are the names we're talking
about right now. And you know to the extent that
there's a broadening out of the market advancement in twenty
twenty five, if we are up on the year, we
welcome that. You look at the equal weight S and
(50:51):
P five hundred today, it's only down one quarter of
one percent today, quite telling, So.
Speaker 3 (50:58):
Forgive me, did you so? Would you are you buying?
Would you be buying an end video? Would you buy
a broadcom? Because they've all of a sudden been whacked
in a big way. If you still believe in them
fundamentally and I'm not sure if you do or I'm
just curious.
Speaker 8 (51:13):
Yeah, we believe in growth opportunities within the technology segment.
We would also argue that there has been a significant
amount of passive dollars flooding into these names, driving them.
If you look at the top seven names of the
S and P five hundred, they're trading over thirty times
(51:33):
forward multiples. You look at the bottom four under ninety
three names trading at seventeen times. So do we think
they're quality companies?
Speaker 10 (51:40):
Yes?
Speaker 8 (51:41):
Do we think that some of them are not trading
at necessarily that the most attractive price point? Yes, and
we think we can be in the affirmative on both.
But we do think too that that doesn't necessarily mean
over the long run that dollars are going to be
accruing significantly away from these hyper scalers. But this broad
opportunity across technology. Even the utility landscape today is quite interesting.
(52:03):
Where this whole narrative around electricity demand, we've been hearing
it for weeks and months. Look at Constellation Energy today,
this is the deal.
Speaker 6 (52:10):
That Microsoft did right three Mile Island.
Speaker 8 (52:12):
That's down twenty percent today, yea.
Speaker 6 (52:17):
Down thirty percent today.
Speaker 8 (52:18):
Look at the water utilities today that no one wanted
to talk about last year. They're up five six seven
percent today. So it's really interesting. This rotation interesting?
Speaker 3 (52:26):
So interesting rotation? Is it an investible interesting rotation?
Speaker 8 (52:32):
Well, I mean, just look at multiples. I mean, are
we gonna Are we going We haven't contracted permitted a
nuclear build out since the nineteen seventies. The markets acting
as though we're going to have a dozen nuclear buildouts
contracted in twenty twenty five. It seems highly unlikely. I mean,
(52:52):
we do think that we're gonna have less regulation. But
even the announcement at the White House last week was
quite quite interesting. Where you know, if you look at
thee hundred billion dollars spend a year for four years,
actually more than that, it's five hundred billion over four
years that was announced to build out AI infrastructure. That
timing looks a little off right now, but to build
(53:12):
out AI infrastructure, the amount of electricity demand for those
data centers would be about one point seven gig a
lots per year based on the dollar spin that they're
talking about. That's about that's that's over. That's about it.
Actually it's two point seven excuse me, that's almost three
nuclear power plants a year just for that project. So
that we were getting I think over our skis in
(53:34):
the marketplace to some extent a.
Speaker 10 (53:37):
Short time.
Speaker 5 (53:38):
Okay, if we're getting over ski if we were getting
over skis now to continue the metaphor, where are we
on the on the slope?
Speaker 8 (53:45):
Well, I think there are plenty of opportunities in the market,
as I mentioned, if you look at forward multiples outside
of this sort of you know, hyper focused area of technology.
We've even in utilities as I mentioned, you know, the
water utilities, they have nice roe growth, they're training at
reasonable multiples. You look at the industrial segment of the market,
(54:07):
we're seeing a lot of opportunity across the board there.
If you look at you know, certain segments of the financials,
we think MNA activity is going to accelerate this year.
Private equity funds have in many cases reached the end
of their life in terms of the limited partnership duration
of ten years or more, and so we think that
(54:30):
these companies are going to need to be either brought
into the public market or sold in back into the
private market this year. Huge opportunities for banks, advisory firms,
companies that work on valuations of private equity. So you
have plenty of opportunity there too.
Speaker 7 (54:46):
All right, Aaron, thanks so much.
Speaker 3 (54:48):
Aeron Kennon He is co founder and CEO Clear Harvard
Asset Management, joining us from Stanford, Connecticut.
Speaker 2 (54:53):
This is the Bloomberg Business Week podcast, available on Apple, Spotify,
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Speaker 2 (00:08):
This is Bloomberg business Week Insight from the reporters and
editors that bring you America's most trusted business magazine, plus
global business, finance and tech news. The Bloomberg Business Week
Podcast with Carol Masser and Tim Stenoveek on Bloomberg Radio.
Speaker 3 (00:27):
Our first guest, he's part of the family, Man Deep Sing.
He doesn't know, but we're not going to let him
go for sixty minutes because there's so much to talk about.
When it comes to Deep Seek, we want to get
into it. As you know, it's the Chinese artificial intelligence
startup Deep Seek, their latest model AI model, sparking a
one trillion dollar route in US and European technology stocks.
We have been seeing this AI shot play around the
(00:50):
globe on this Monday. A lot of questions though about
maybe valuations here in the United States, but what it
really means in the AI race. So let's get to it.
Man Deep is Bloomberg Intelligence Senior Tech industry unless Man
Deep seeing he's here in studio. You've been up early.
We've been listening to you, both Tim and I throughout
the day. Why is this all happening? Because for your world.
(01:13):
You guys, this has been on your radar, But why
is it all of a sudden on our radar and
why should we care or shouldn't we care?
Speaker 4 (01:19):
Well, every company has been talking about how capex needs
to go up because they believe in scaling laws. I
think what this development has shown is the hardware that
these companies have procured, they weren't using it efficiently and
literally it's both on the training side as well as
the inferencing of the models when it comes to using
(01:42):
it in chatbots and so on. And that's where I
think you have to ask yourself as an investor, are
you ready to pay up for these companies when they are,
you know, increasing their capex when we know they're not
running it efficiently. So I think a lot of questions
around just the efficiency of the hardware. I mean, the
scaling will continue just because there is more demand to
(02:03):
incorporate AI, but the fact that you know this model
does it so much more efficiently, I think raised a
lot of questions.
Speaker 5 (02:11):
Does it show that deep Sinck is actually ahead of
open AI, of Anthropic, of Lama at Facebook?
Speaker 4 (02:20):
No, In fact, they are using the output of open
AI and Anthropic and Lama to train their own models.
So think about this, Deep Sea. Didn't you know, train
this model from scratch the way open ai did. They
used output from open AI's models to train its own model.
(02:41):
So in effect, they are paying open ai, you know,
for all the API calls. But then they didn't have
to do things from scratch. And that's where you know,
if you are a meta Llama who has invested billions
of dollars in creating LAMA model, what was their incentive
to open source it to begin with? Because open sourcing
it made it easy for someone like deep Seek to
(03:02):
build their own model. And that's the thing about open sources,
you lose your IP. Someone else can come up with
a better approach to do things more efficiently, and suddenly
everyone runs to them.
Speaker 3 (03:14):
Man, Deep is this like the Apple Store. You don't
have to be first, you just have to be better.
Like I'm thinking about like creating a smartphone.
Speaker 4 (03:21):
I won't compare them to Apple yet, I mean, they'll
have their problem when it comes to distributing this model.
There's no way I can see, you know, Deep Seek
getting to the adoption of open Ai, especially here in
the US. But at the same time, you have to
give them credit for you know, just being novel in
terms of you know, the limited GPUs they had and
how they ended up using them.
Speaker 3 (03:42):
Do you trust the information, the research, and do you
trust that what they say they did they did do?
Speaker 4 (03:50):
Probably not. If they are saying six million dollars for
training their entire model, I don't trust it because when
I look at OpenAI costs for training their you know,
GPT four model, it was close to three hundred million.
Speaker 6 (04:03):
So we are talking about a fifty x gap.
Speaker 4 (04:06):
Now, even if Opening Eye wasn't very efficient, I don't
buy the fifty x gap. So clearly, you know there
is something that they are not counting when they you know,
release the paper. But at the same time, they've give
given us enough evidence to show that they are doing
things much more efficiently on the hardware side because of
the constraints they had Men Deep.
Speaker 5 (04:27):
I know you don't cover in video, and we're gonna
be speaking to Ian King in just a few minutes,
who's been covering in video in the ship space for years.
But we can't ignore that in videos down close to
eighteen percent right now. I mean it's shed almost a
fifth of its value in just today. Yes, the run
up over the last couple of years has been immense,
but a day like today is just mind boggling. I
think for a lot of people should in video in
(04:47):
your view be worried.
Speaker 4 (04:49):
I mean, look, that's where a lot of the questions
come is the cost for training the next model. So
if deepseek is saying that the cost was six million,
I think it should be really worried. But a lot
of people are apprehensive of that six million number because
they think it'll be higher. And it won't be three
hundred million the way open Aies was, but it will
(05:10):
be higher. And that's where I think open Ai or
Entropic will have a very tough time selling to their
investors that they need to build a one million GPU
cluster to train the next version of their model.
Speaker 7 (05:23):
Mandi, does this show that even though the US has been.
Speaker 3 (05:28):
Pretty rough in terms of restricting advanced technology, going over
to China, does this show that Chinese R and D
and Chinese companies can be pretty scrappy and pretty smart
and maybe figuring a go around and coming up with
their own way of competing against Nvidia.
Speaker 8 (05:42):
And the like.
Speaker 4 (05:43):
Yeah, and look, I think this could be another way
of them saying Look, we are open sourcing whatever we
have learned so far. So they want to build a
community because the export restrictions aren't going away, so they
are not going to get the you know, black ball
chips on paper and all the other allocation. And the
thing about model training is it's continuous. It's not a
one and done thing. So you have to continuously improve
(06:05):
your model. The other labs will go ahead if they
are not able to, you know, keep doing the training
and all the other stuff that other labs are doing.
So from that perspective, I think the whole aspect of
community building is front and center here. Yeah, but I
still think the cost parity is a very big concept here.
Speaker 5 (06:23):
Hey, before we let you go, Mandy, you do cover
meta platforms. The company out on Friday, Mark Zuckerberg saying
he was going to be spending more on Capex than
previously announced. Then the stock moved higher on Friday. Stock
was lower earlier in the session, but higher now. I mean,
I look at a move like that today and that
runs counterintuitive to kind of everything we're talking about.
Speaker 4 (06:43):
Look, there is a lot of confusion, but if there's
one thing that happened today is this moment is good
for open source, and meta Lama is an open source model,
so if anything into open source does get a nod
when it comes to you know what deep seek is
touting here.
Speaker 3 (07:00):
But you do also think about if it's cheaper for
companies to build out, then does everybody have to rely
on some of the bigger players.
Speaker 7 (07:07):
Maybe not.
Speaker 4 (07:07):
Next time Meta Lama will collect a fee from deep
seek for you know, using their model to train their
own models, so that could be a positive.
Speaker 3 (07:15):
I love this world that keeps us on our toes men,
deep saying keeps us on the straight and narrow. He's
Bloomberg Intelligence senior tech industry analyst here and has been
all over this story. We want to focus a little
bit more on semiconductors because we have seen that group
really taking a beating. You've got almost all thirty names
twenty eight out of thirty down in the Philadelphia Semiconductor
(07:36):
Index down about ten percent, the index as a whole.
Nvidios down seventeen percent. So ouch, what does this mean
for Nvidia specifically? We get to now Bloomberg News US
semiconductor and networking reporter Ian King. He's out there in
San Francisco. I don't know Ian, how we've all been
like talking about this non stop today you're the expert.
How are you thinking about Nvidia and possible impact the
(07:57):
reality of it all?
Speaker 7 (07:59):
How do you see it?
Speaker 9 (08:00):
I mean a lot depends upon how much reality there
actually is behind this claim behind you know, it was
a very well set out, well referenced research paper at
this point, and the model has been open sourced and
we'll see what people can do with it. The implication is,
of course that things got cheaper, things got more simple,
(08:23):
but we'll have to see that manifest itself in the
real world. And then obviously you can absolutely bet that
in video and a lot of other computer scientists that
some of the most powerful companies in the world are
looking at this right now working on this. For some
of them this would be great news. For others it
would be a disaster. So they'll be definitely testing out
(08:43):
the veracity of this, and I think the actual where
the truth lies will emerge with a bit more time.
Speaker 5 (08:50):
In What do you make of selloffs in other names
today Broadcom, for example, Marvel, I mean everybody is getting
hit in the sector. As Carol mentioned, twenty eight of
thirty names lower.
Speaker 9 (09:01):
I mean, yeah, yeah, the logic is absolutely clear, right,
I mean, if you are no longer a believer in
this exponential growth in spending, in this exponential need for
more and more computing, then you're going to sell Micron,
You're going to sell broad Coom, you're going to sell Marvel,
and of course you're going to sell in video or
(09:23):
you know. The logic based upon an assumption, and that's
what it is at this point is flawless. I mean,
for example, Broadcom, they are the key ingredient in terms
of these companies like Google that are now designing their
own chips for this type of purpose. So if there's
going to be less need for that kind of high
(09:43):
end chip, then it makes sense to sell them.
Speaker 3 (09:45):
I mean, none of this happens in a vacuum, right,
so I can only imagine the meetings that are happening
at Nvidia today and all of the chip companies. So
would you expect them to, you know, you know, tear
apart the research from this and try to understand exactly
what they did and then come back with their own response.
Speaker 9 (10:05):
You've got I mean, they've got to do that, right,
I mean, the the you know, if this was a
two or three percent move and a few market jitters.
Then you know you probably as a management team you
look into it fiercely, but you just keep your mouth shut.
Or we're just about to go into earning season, right,
So whether they like it or not, for example, Intel
on Thursday are trying to get into this market, They're
(10:26):
going to get asked about this.
Speaker 10 (10:28):
What have you got?
Speaker 9 (10:28):
How can you deal with this? Is this good for you?
These are all questions that I think, you know, everybody's
companies are going to be answering over the next two
or three weeks, and they better have some good answers.
Speaker 5 (10:39):
And do folks you taught you speak to who are
covering the industry, have they been waiting for a day
like today?
Speaker 10 (10:46):
Like was this bound to happen?
Speaker 9 (10:49):
I mean, you know, investors do two things right. You
have different types of investors, but basic pattern recognition is
supposed to be the skill that everybody can bring to this,
whether your technical or whether you're just a you know,
a general investor. So I think a lot of the
general investors will be like, let's let's not be on
(11:10):
the wrong side of what happened in two thousand with
all of the Internet sell off. Let's get out right now, right,
maybe we're at the peak. More sort of technically savvy
investors will probably take their time look at this and
try to find out just how much truths there is
there and just how many concrete implications there are.
Speaker 7 (11:28):
Well in terms of implications too.
Speaker 3 (11:30):
You know, a lot of what's been kicked around throughout
the day is you know, I feel like TikTok, you know,
version two point zero in other words, another Chinese company.
You know, you want to know how much the government
is involved and how much maybe you know, do they
support the r indeed, siphius from the United States, the
Committee on Foreign Investment in the United States, you know,
are they going to weigh in on this whether or
not you know, American companies or you know, can tap
(11:53):
into it. I mean, it's a whole other round of this,
it seems.
Speaker 11 (11:57):
Yeah.
Speaker 9 (11:58):
No, I clearly there's a lot of scrap rambling going on.
And you know, the path that's happened so far in
that particular area has been to restrict access to these
high end chips. So guess what, the country that is
restricted from these high end chips suddenly comes up with
the magic bullet solution, which says, maybe we don't need
as many of these high end chips, or maybe we
(12:19):
don't need them at all. So there is an element
of like, hmm, okay, is this really Is this the
answer that they want us to be concerned about, or
is this really the answer? Or have we given them
so much incentive to find a way around it that
they've poured all their energy into it being really smart
and got around it. I mean, layers upon layers of
(12:39):
things going on here, but in general, there are no
magic bullets in at least the chip industry. It tends
to be a pretty incremental industry where we see changes
over time. Software can be more volatile and you know,
is prone to more kind of instant changes in thinking.
But even then, and you know, the change to a
(13:01):
whole industry, the direction that's going in, it's a little
bit hard to imagine that one morning we all wake
up and go, oh dear right. But at the same time,
if you're an investor, you can't afford to ignore the possibility.
And if you're the CEO of in Video or the
board of InVideo or the senior management of video, you
cannot afford to ignore the possibility.
Speaker 5 (13:23):
Ian on a day like today, you know, we're certainly
focused on the big names that are moving lower by
double digits in video, certainly down Broadcom is lower today,
Oracles down by fourteen percent.
Speaker 10 (13:37):
But from a.
Speaker 5 (13:38):
Hardware perspective and from Deep six perspective, what do you
know about the hardware that Deep seek users to train
its own?
Speaker 9 (13:46):
That's no, and that's that's a very good question. That's
probably one that the US government are looking into, which is,
you know, some of the analysis that we've seen has
been like, look, yes, this model that they're citing that's
actually a derivative of another model. How did they train
that original model? So should we classify this derivative model
(14:07):
that they're offering up as part of this larger equation
which they must have developed with Western technology? And the answer,
simple answer is we do not know. And there's going
to be a lot of pressure on those that need
to know and should know to find that out. And
I think we're going to see a lot of reporting emerge.
(14:27):
We're going to see the government looking into this to
find out what did they have access to, should they
have had access to it, if what they had access
to was in fact more efficient computing than what say,
Microsoft is putting in place. Then wow, here we go. Right,
this is a breakthrough so many layers to this onion,
and that's not a very useful conclusion, but I think
(14:48):
it's the best that we can offer at this particular point.
Speaker 7 (14:51):
A lot of questions still out there. Ian, Thank you
so much, so appreciated. Of course.
Speaker 3 (14:54):
Our Bloomberg News US Semiconductor and Networking reporter.
Speaker 1 (15:00):
Is the Bloomberg Business Week Podcast. Listen live each weekday
starting at two pm Eastern on Applecarplay and Android Auto
with the Bloomberg Business App. You can also listen live
on Amazon Alexa from our flagship New York station, Just
say Alexa Play Bloomberg eleven thirty.
Speaker 3 (15:17):
It feels like the last week or so, topped off
by today's news on Deep Seek, has put the AI
story once again tim front and center in a super
big way.
Speaker 10 (15:25):
Yeah.
Speaker 5 (15:25):
Remember just last week, President Trump any group of tech
companies SoftBank, Oracle and open Ai initially planning to invest
one hundred billion dollars to build US based infrastructure, including
data centers for open Ai, the project we know called Stargate.
On that though, one very high profile tech and administration
voice who's not all in on it It's something that
Bloomberg BusinessWeek columnist Max Chaffkin gets into in his latest
(15:47):
story and in the latest Bloomberg BusinessWeek daily newsletter. You
can read Max's business Week story on the Bloomberg and
at Bloomberg dot com slash BusinessWeek. Max the co host
of the Lining podcast, also the author of the concheriont
Peter Tiel in Silicon Valley Pursuit of Power. Max, We're
gonna talk about elon Stargate in just a second, but
deep Seek is where I want to start because it's
(16:08):
what's hitting the tech names today. Well, I don't want
to say all tech names. It's what's hitting you know, Nvidia,
Broadcoms and of the other chip names in a big
way today.
Speaker 12 (16:16):
How are you looking at absolutely well, you know, as
you're hinting at with this discussion of stargate, until basically
this weekend, you know, AI infrastructure was seen as.
Speaker 6 (16:25):
The end all be all.
Speaker 12 (16:25):
You know, they were talking about not not one hundred billion,
five hundred billion, right and at times Sam Altman has
said he's gonna he's gonna need seven trillion dollars in
you know, funding for AI infrastructure, and there's been this
sense especially among Google, Open Eye, a bunch of these
big players, that this is gonna be the thing that
(16:46):
like only hyperscalers are going to be able to compete
in that whoever has the most infrastructure, even whoever has
the most power. Right, We've seen a big run up
in nuclear stocks and things like that, so so, and
this sort of threw all that out the window because
if we're to believe what deep seek is saying, this
was done with a much much lighter weight, uh you know,
amount of usage of chips and it and it actually
(17:08):
is running a lot more efficiently efficiently. So that suggests,
right that that these this crazy run up we've seen
in demand for GPUs and so on might be overheated.
And we we had other reasons to think that there
was perhaps some sort of bubble or a little bit
of frothiness in this market. And and I do think
if it hadn't been this, it might have been something else.
Speaker 10 (17:28):
Right.
Speaker 6 (17:28):
I think investors were and are primed.
Speaker 12 (17:31):
To see, you know, to see to see potential flaws
and with the with the business model that so many
have bought into.
Speaker 3 (17:38):
So not necessarily an end of like the AI spend,
but just kind of a twist and turn in the story.
And there's still more to be known, right Max, in
terms of the reliability of the information we're hearing from
them and the reality of it.
Speaker 12 (17:49):
Yeah, there's so much we don't know here, and again
it's definitely worth I think approaching Deep Seek's claims skeptically
and also understanding that there if they were able to
develop a much more inexpensive model that could help parts
of the AI market. It doesn't necessarily mean that all
of this goes away or something, but it may.
Speaker 7 (18:10):
Make it more accessible, right, that's less expensive.
Speaker 12 (18:12):
Yeah, it definitely, but it could cause investors to like
dramatically revalue like some of their assumptions.
Speaker 5 (18:18):
How does it change the narrative around what China is
able to do when it comes to AI right now
and sort of the tech race that's happening there. The
thing is, if they weren't supposed you know, there are
these chips, A lot of these chips are not supposed
to go to certain parts of the world.
Speaker 12 (18:30):
Right, So that so there's something potentially troubling there. If
you're if you're looking at the attempts to restrict certain
US technology to China, it seems like either those restrictions
aren't working that well, maybe some GPUs found their way
to China, or or that the Chinese software industry has
found ways around it, which would also be potentially problematic,
(18:54):
I suppose from a sort of US national security perspective,
at least from the point of view of the China
Hawks who have been sort of warning about this, and
that includes many of the Silicon Valley companies like remember,
one of the big reasons to justify this, like massive
spend on AI And one of the reasons that many
of these folks, including Sam Altman, sees this as a
(19:15):
thing that government should be involved in, is because they
have been arguing that without this, without spending huge sums
of money on say on power or investing in infrastructure
in terms of data centers, that we would fall behind
behind the Chinese tech startups. And that may you know,
if you sort of extrapolate from this very small piece
of news, you might say, Okay, well it's happening anyway.
(19:37):
So that sort of throws everything into a bit of disarray.
Speaker 7 (19:40):
All right, So let's get to stargate. Love the name,
love the name Elon Musk. I find it interesting. I
think we all found it interesting.
Speaker 3 (19:48):
That here's this big announcement right that comes out of
the Trump administration last week, and Elon not so in
on it?
Speaker 6 (19:55):
Is he no, not in on it at all.
Speaker 12 (19:57):
You know, it wouldn't be surprising if if you had
this big announcement with Donald Trump and the CEOs of
some major companies talking about huge numbers, right they were saying,
we're going to invest one hundred billion dollars immediately five
hundred billion with the next four years, would not have
been surprising if some people said this sounds like a
political stunt, I'll believe it when I see it. It's
(20:17):
what made this thing that happened last week so surprising
is that the person saying that was a senior advisor
to Donald Trump, and it was Elon Musk.
Speaker 6 (20:26):
Tweeting over and over and over again last week.
Speaker 12 (20:29):
I mean, the last time I checked, twenty times, he's
tweeted a few more times. You know, the usual mix
of i'd say, off color jokes and put downs. You know,
he's called Sam Altman, who was of course on stage
with Donald Trump, a swindler. He suggested the announcement was fake,
and Trump has sort of responded by saying, hey, you
know Elon Musk has a dispute with one of the
(20:50):
people in this in this deal, which is true.
Speaker 6 (20:54):
Sam Altman and Elon Musk have.
Speaker 12 (20:56):
Been feuding more or less in public for the last
couple of years, So we're sort of seeing I'd say,
you know, maybe one of the downsides to having somebody
who is as deep in the business world also involved
as a advisor to the president.
Speaker 5 (21:10):
I mean, is Elon Musk at this point saying, Hey,
I gave you some giant bags of money to help
you win the election.
Speaker 7 (21:15):
What were you thinking?
Speaker 5 (21:16):
And now you're doing this? Does this risk driving a
wedge between the two of them?
Speaker 6 (21:20):
I think for both Musk and Trump.
Speaker 12 (21:23):
I mean, there has been over the last couple of
months people who have been hot on high alert for
signs that this relationship might be might be breaking up.
And I would say that it doesn't seem like this
has done it either. You know, you know, Trump has
cracked jokes before, We've seen these tweets. There have been
there was a dispute over the H one B visa
thing both Musk.
Speaker 5 (21:43):
And maybe that led to the divorce between Ramaswamy and Musk.
Speaker 12 (21:46):
Yeah, yeah, at least according to some reports. You know,
it's possible there are other reasons as well. But but
what I'll say is it seems like Musk and Trump
are still working closely together. I'd say Trump's comments about
this to me suggested that he was untroubled by Musks,
you know, apparently kind of trying to undermine or or
undermine some of his partners in this deal. And I'd
(22:07):
say part of that is that, you know, there's not
necessarily government money going into this. In the Stargate thing,
it really was basically a media event for Donald Trump
to announce a big business deal so that he can
claim credit for, you know, helping to spur the economy.
It's kind of like a vibes thing. And I think
because of that, I'm not sure it really hurts Trump
(22:29):
all that much to see Elon Musk dissing Sam Altman
on Twitter.
Speaker 3 (22:33):
Well, you write in your story, Max, you said Musk
has always treated his conflicts of interest like features rather
than bugs, seeming to run his normally independent companies with
their nominally independent shareholder basis as if they were a
single conglomerate. You talk about employees being lent out, sharing
of resources and stuff.
Speaker 7 (22:49):
So conflict he's kind of all in on this too.
Speaker 12 (22:52):
Well, yeah, absolutely, this is a big part of First
of all, competing in this area is a big part.
Speaker 6 (22:59):
Of Elon Musk's big plan for.
Speaker 12 (23:01):
His companies, not just Tesla, which of course is developing
you know, advanced robotics and is trying to build self
driving cars, but also x Ai, his his chatbot competitor,
so he is very much playing in this market. He
is also competing to buy these Nvidia these high end
in Nvidia GPUs. He's building giant data centers, so he
(23:23):
very much has a dog in this fight, and that's
why he's doing this. And I think Trump's attitude seems
to be that's all out in the open, as long
as people understand that what's behind this is a business dispute.
Speaker 6 (23:36):
Again, he said, well, one of the things is.
Speaker 12 (23:38):
Is he hates one of the guys in the deal,
an obvious reference to Elon Sewings and but then Trump said,
you know, I hate people too.
Speaker 7 (23:47):
So we all have a problem.
Speaker 11 (23:49):
Child.
Speaker 5 (23:50):
I wonder you know what what Donald Trump has been
able to do in recent months has been pretty incredible
when it comes to the tech industry. I mean a
week ago, Carol and I were sitting here looking at
the stage and during the inauguration, and you saw titans
of industry who were not at previous inaugurations there all
collectively getting behind the president. I mean, he's he is
this larger than life figure who perhaps can bring people
(24:11):
together who don't like each other, maybe because he offers
them something that they want.
Speaker 12 (24:18):
Yeah, well, Trump probably more so, at least than than
foreign President. Biden approaches the presidency in a way that
I think would be fair to describe as a little
bit more transactional.
Speaker 11 (24:27):
Right.
Speaker 12 (24:28):
He's willing to bend his policies to make deals. It's
the whole thing that he's about, and in certain ways,
right that works well for CEOs.
Speaker 6 (24:37):
I also think there's a lot going on there.
Speaker 12 (24:39):
There was a lot of built up anger in Silicon
Valley over some of Biden's policies over anti trust for instance,
and you have a lot of opportunism right now. There's
a sense that they have leverage because by showing up
in these Trump things, they they're giving Trump some additional
credibility and they're trying to use that to get you know,
what they can, which is, you know, favorable policies, favorable
(25:01):
and trust policy.
Speaker 7 (25:02):
We're going to talk about that in the next couple
of hours.
Speaker 5 (25:05):
Hey Max, do you want to go back to where
we started and deep Seek because we're getting some breaking
news and video is out saying that deep seek is
quote excellent AI advancement and says that deep Seek's work
quote fully export control compliant and says that inference requires
significant numbers of its GPUs. This is an email statement
on the deep seek AI model. They're they're coming out
(25:27):
and saying talking about it. I'm wondering how you view that.
Speaker 12 (25:30):
I mean, I think it's first of all, everybody's talking
about it. It seems like it seems like they that
they have to and they also I think in that
statement and I haven't looked at I'm just hearing it now,
it seems like an attempt to address suggestions that perhaps
deep seat Seek had access to you know, improper access
to GPUs or something like that.
Speaker 6 (25:49):
It sounds like they are saying, no, that's not the case.
Speaker 12 (25:52):
Again, it definitely seems like this would be a business
challenge for for Nvidio if you were if you were.
Speaker 6 (25:58):
Able to do the kinds of hatbot.
Speaker 12 (26:00):
You know, work much much more efficiently with about the
same sort of level of quality that's gonna make these
GPUs perhaps not as valuable.
Speaker 6 (26:11):
But again a lot. There's a lot here that we
don't know.
Speaker 12 (26:14):
And you also have seen people on the other side
of this saying, actually, this is going to be great
because it's gonna make these chatbots so much cheaper. We're
gonna see tons of them. Essentially, we're gonna make it
up on volume. It's hard to know how to evaluate that,
and we don't know that much about how this was
put together or really just how good the quality looks.
People have been playing with it only for a short amount.
Speaker 3 (26:35):
Wait you want details. Excilly you great stuff, Max, Thank
you so much. Bloomberg Business Week commnist Max Chafkin is
also co host of the Elon Inc.
Speaker 7 (26:44):
Podcast.
Speaker 13 (26:44):
You could check that out.
Speaker 3 (26:45):
It's on the Bloomberg and also at Bloomberg dot com
slash Elon Inc. Max is also author of the contrarian
Peter Teel and Silicon Values Pursuit of Power.
Speaker 2 (26:56):
This is the Bloomberg Business Week podcast. Listen live each
week day starting at two pm Eastern on applecar Play
and Android Auto with the Bloomberg Business app. You can
also listen live on Amazon Alexa from our flagship New
York station. Just say Alexa played Bloomberg eleven thirty.
Speaker 3 (27:13):
Hey, I guess say reading in this morning, Morgan Stanley
continues to recommend that investors hold long five year treasuries
ahead of two potentially devish market catalysts. And those catalysts
are the January FED meeting, So not this week's meeting
and then this month's job report. Meantime, you've got jp
Morgan stay staying along the front end of the treasury
curve well Bimo positioning for two quarter point FED cuts
(27:36):
this year. So while we are focused so much tim
on tech and AI news this morning, let's not forget
we at the first FED decision of twenty twenty five,
That decision out on Wednesday.
Speaker 10 (27:44):
Okay, with more on that, With.
Speaker 6 (27:46):
More on that.
Speaker 5 (27:46):
In the studio, we got Ian Wyatt's senior vice president
director of Economics at Huntington Commercial Bank. It's a division
of the publicly held roughly twenty five billion dollar market
cap Huntington Bank. Shares Ian, good to see you. Look
before we jump been to exactly what we're going to
hear from Fed sho Jpowell, I would imagine he might
get some questions around AI and the market sell off
(28:07):
this week. Whether or not he answers those questions, that
certainly remains to be seen. I would figure out a
way to ask him a question around that, How do
you think, how are you looking at what's happening in
the market this week, especially ahead of this FED meeting?
Speaker 14 (28:20):
I think, well, first, I think in terms of the
FED meeting, not related to AI, I think long our
view is that there's still inflationary pressures out there in
the economy when I taught, but I think it's really
we have this two speed labor market we're seeing. We're
seeing is for lower end jobs. You know, where's the
job growth been. It's been restaurants, it's been hotels, It's
(28:41):
been a lot of service areas. And when I talk
to companies in those areas, whether you're manufacturing, transportation, still
a tight labor market. They're having a hard time finding workers.
If you're talking about more of a college job, professional
and business services, where are we not getting job growth?
Speaker 10 (28:55):
It obviously has been down.
Speaker 14 (28:56):
We've seen you know, them focusing on cash flow more
than job growth. So we kind of have this this
two speed labor market where you still have a tight
lower end, and the problem for inflation is a lot
of those industries are very labor intensive.
Speaker 10 (29:10):
You know, childcare for example.
Speaker 14 (29:12):
It's something where labor or restaurants, labor makes up a
huge percentage of your cost structure, and they're still feeling that pressure.
So I think we've probably been on the low end
of the FED saying in terms of cuts for twelve
months now. Yeah, now I think we're more in line
with the two cuts roughly this year. But I still
think that pause holds for a while because I think
(29:34):
there is that fundamental underlying inflationary pressure that is not
really when you tease out inflation, you look category by category.
Speaker 10 (29:43):
It's not been durable goods.
Speaker 14 (29:45):
Durable goods have been coming down, but it's also stuff
that consumers can choose not to buy.
Speaker 3 (29:49):
So I just want to stay with AII for a moment.
That AI spend the economic you know, activity, it may
impact on the upper down side. You know, how does it,
if at all, factor into any of your ex economic
models when it comes to growth, when it comes to inflation,
and then ultimately to FED policy.
Speaker 14 (30:04):
You know, AI caused me to get one call really
wrong last year. It was I thought construction employment was
going to come down. Yeah, I thought, you know, multifamilies
coming down. We saw warehouse space is over supplied. Now
obviously office has its issues, and I underestimated how much
it would be chipsacked.
Speaker 10 (30:20):
It would be the.
Speaker 14 (30:21):
Chip plants like Columbus for example, or we're headquartered. They
have that massive intel plant, a couple of the largest
cranes in the world operating there. And AI was a
huge part of this. And I still think there's this
huge first mover advantage. You don't want to be the
last company. You want to be the last company that
still gets a power connection versus the first where they
(30:41):
say no, we don't have enough juice, we can't afford
or we can't build, you know, connect you for five years.
Speaker 10 (30:48):
And I think that that case still remains.
Speaker 6 (30:51):
Yeah.
Speaker 14 (30:51):
I also think there's another bullish case for power that
when you look at the forecasts and really baked invert.
Speaker 10 (30:56):
What is that about? Transportation?
Speaker 14 (30:58):
So so, okay, if you look at US energy consumption,
roughly fifteen percent of US energy consumptions residential, that's what
we always think of our power. Thirty seven percent of
US energy consumption is transportation. Right now, over the last
six months roughly ten percent of US car sales we're
up to have been plug in vehicles now. Vehicle fleet
takes a long time to turn over in the US
(31:19):
average vehicle ages over twelve years now, it takes a while.
But as that starts to kick in, if EVE even
got a small fraction of that thirty seven percent shifting
from fossil fuels to electric power, it doesn't really matter.
Speaker 10 (31:33):
The source, whether it's gas or solar.
Speaker 14 (31:35):
Or whatever, you have a very different outlook for electric
demand at the US. And I think that also means
utilities are going to have to build a ton of infrastructure.
Speaker 5 (31:44):
Does that get derailed by the Trump administration pushing back
against EB subsidies and moving trying to get people to
move away from evs.
Speaker 14 (31:51):
I mean, I think it slows it to some degree.
I think that's definitely. You know, you're seeing a shift
administration policy. If you look at Germany, for example, when
they cut their TV subsidies, that dramatically slowed EV's sales.
But it's still something where there's a lot of the
global market is shifting in that direction. Autos are shifting
that way.
Speaker 7 (32:11):
China's all in, China's all in.
Speaker 14 (32:14):
I mean, you talked to a friend of mine runs
FedEx distribution, owns a couple of Fredecks distribution places, and
he talks about, you know, the gas prices on his
delivery trucks, and he's really looking, how do I lower
my fuel expenses? And that's really a perfect application for
EV short range so stop start driving?
Speaker 10 (32:32):
So does he do that with Rivians?
Speaker 14 (32:34):
Like yeah, I mean he's looking at Yeah, he's looking
I mean, Rivian's just starting to sell beyond Amazon now,
they're just moving beyond Amazon or filling those initial orders,
whether it's that or Forward and Stillantis both have products
in that market as well.
Speaker 10 (32:50):
Sorry here, I know we're supposed to be talking about.
Speaker 3 (32:51):
The I kind of love this because it's a fuller
picture of kind of the markets and really our economy.
So having said that, I mean, I don't know this
January meeting, the decision on Wednesday Ian, is it kind
of a snoozer because we don't really expect anything? Or
is there a fine noodle, a noodle, a fine needle
that j Powell has to thread here?
Speaker 14 (33:11):
In some ways I think thematically we've seen you know,
a year ago when he did the Palll pivot, you
felt like there was pushback right after he spoke at
that presser, and it definitely seemed like he was on
the duvish end of the spectrum. If you look back
at the September vote on the dot plot, you can
see almost half of Fed Governor's only wanted three cuts
this fall. So that would mean essentially there should have
(33:33):
been one twenty five in each meeting, and that meant
they were opposed to fifty in September. Now, obviously they
all get in board, they all push in the same direction,
but if you look at the minutes, you look at
the notes, I think he's still again. I think this
is a repeat of about a year ago. It's he's
on the dubvish end of the spectrum. He has to
get the board to come along with him. And I
(33:53):
don't think I think. I think the inflationary pressure is
still there. I still think there's some underlying and when
I talk to companies in the economy, depending on the
part of the labor market they're in.
Speaker 10 (34:05):
It's still there.
Speaker 14 (34:06):
It's it's still significant, and I think that helps some
of the more hawkish voices on the FED, where the
very narrowly balanced FED I think on this.
Speaker 3 (34:15):
So it's really labor costs that you're most concerned about.
It's not the price of eggs that everybody keeps talking about.
It's really labor costs.
Speaker 14 (34:23):
Well, yeah, I mean, I'm the grocery shopper in the family,
so I definitely noticed the price of eggs. And I
know used to work in Georgia, so I know, you know,
top egg economy, top egg producing state in the country
is basically offline right now because of bird flu. So
there's some big things going on there. But now I'm
much more concerned about rent growth. I mean, that's a
good sign we're seeing on the inflationary front. If you
(34:43):
look at the market based rent indexes, you can see
you're at one one and a half percent. The problem is,
you know, two thirds of Americans on their home A
lot of that single family we're still seeing and the
implicit rent deflator from that comes from rents on single family,
not multi family, and that's still feeling pressure.
Speaker 7 (35:01):
What did you want to say, I know I jumped in.
Speaker 5 (35:03):
Oh, I just I wanted to just say in videos
down eighteen percent, everybody, that's the that's the day. Looking
at Broadcoms down eighteen percent, Oracles down seventeen.
Speaker 7 (35:13):
Percent, but no inflation there.
Speaker 10 (35:16):
Then that's a backdrop of some would say.
Speaker 3 (35:18):
It's on sale or maybe not, depending on the outlook.
This was really fun. Come back soon and why are
senior vice president and director of economics loved where the
economic conversation went over at Huntington Commercial Bank.
Speaker 7 (35:29):
Joining us here Tim in studio.
Speaker 1 (35:31):
You're listening to the Bloomberg Business Week podcast. Catch us
live weekday afternoons from two to five y's during Listen
on Applecarplay and Android Auto with the Bloomberg Business app,
or watch us live on YouTube.
Speaker 5 (35:45):
Susy dan Is Cudy of America's over at Wi Bro.
It's a global consulting firm that provides services related to
IT cloud and yes AI. And that's really what we
want to talk to her about because that is why
we're seeing the selloff concern that a cheaper AI model
from the Chinese startup Seek could make valuations of these
tech that has powered the bull market pretty tough to justify.
It's what we spoke to Gena Martin Adams about just
(36:07):
a minute ago. Suzanne joins us from East Brunswick, New Jersey. Susanne,
you are just back from Davos, where we know AI
was front and center. Given comments that we areed from
Alexander Wong, who is the founder at CEO over at
Scale AI, how would you though characterize the AI conversation
that was happening over at Davos.
Speaker 11 (36:26):
Well, thank you both for having me. Everything was AI
last week. You could walk down the street and every
storefront had something about AI or was talking about AI.
Speaker 13 (36:36):
So it was front and center.
Speaker 11 (36:38):
This is clearly a defining year for AI and for
jen AI, and businesses are looking to figure out how
do they drive value from this. Most CEOs believe that
it's going to significantly change the way they do business
in terms of how they create and deliver value and
obtain value from the work that they do. And there
(37:01):
was a clear momentum around, you know, defining the strategy
in which they're going to invest in AI to create
that value.
Speaker 3 (37:08):
Why do you think it's that they were saying or
why is it that this is going to be a
defining year, especially on a day when we kind of
just got you know, a company that might say, hey,
you don't need to do the big span or you know,
we can do it. It's a different maybe financial model
in terms of the buildout, I feel like we're still
kind of finding our way. So why why is it
(37:30):
that twenty twenty five is the defining way. I'm not
quite sure how to read that.
Speaker 13 (37:33):
Well.
Speaker 11 (37:34):
I think last year everybody was talking about AI and
just piloting with genai. It was, you know, it became
it's democratized. Everybody has access to it, we can use it.
I think the GENAI races and during a new phase.
We saw it this morning and I think we're still
in the beginning, you know. To me, it really calls
to everyone that this emphasizes the pace we're going to
(37:55):
see innovation and really figuring out how we can create
agile and environments to deliver on AI. And at the
end of the day, it's going to be about the
quality of the data that these AI are trained on
and deliver for our clients to really deliver value to
the organizations, regardless of how much they spend. And I
think you know where we see it is our clients
(38:16):
really are talking about the data they need to fuel AI,
whether it's a large language model or a small one.
Speaker 5 (38:22):
I'm just just for context, because we do speak to
a lot of folks who run consulting firms or run
parts of consulting firms. Just give us an idea of
your clients, the type of clients you have, and you
know who's out there working with you.
Speaker 13 (38:34):
Yeah, so I work, so my responsibility.
Speaker 11 (38:35):
I have clients across financial services, oil and gas, energy
and utilities, high tech, and manufacturing and automotive. So I
have clients across many different industries and many different challenges
that can be solved with them without AI.
Speaker 5 (38:49):
So who would you say is leveraging AI the best
right now?
Speaker 11 (38:52):
Well, you know, AI is a proven and it's been
around for ten years. We've been using in AI, and
many of our financial service as clients have been using
AI and machine learning models for years. It's only now
with GENAI we're seeing this acceleration and that's what's truly
exciting is how we can leverage the genai applications. You know,
we've been also leveraging it internally so that we can
(39:15):
learn and then deliver those learnings to our clients. We're
leveraging in HR, we're leveraging it illegal across the board
to make sure that we understand how AI can be
used and understand the foundation and the governance and responsible
nature in which we need to deploy it and train
our people to make sure that it's successful.
Speaker 3 (39:35):
So, Susan, what I'm wondering is like on a daylight today,
where this story a company that nobody had really are
I should say nobody because our Bloomberg intelligence teams like, yeah,
our team overseas has been writing about deep Seek for
you know, the last couple of years, so it's not
necessarily new to them, but certainly new to I feel
like our conversations when it comes to AI in general.
Speaker 7 (39:55):
So I am.
Speaker 3 (39:55):
Curious, have you guys your team, you know your phone's
been ringing today's say, wait, what is this deep Seek?
And you know I've been spending X on my AI
infrastructure build or you know, making plans? Do I need
to rethink it? Do I not need to spend as much,
you know, on site versus not? You know what tell
us about today and the conversations perhaps that you guys
(40:18):
have all been having.
Speaker 11 (40:20):
So today it's all over the news. It's absolutely correct,
everyone's talking about it. I think the reality is over
time there's going to be winners and losers. You know,
the role that we play is helping our clients make
sure they have the foundations in place. One of the biggest,
and I'll go back to it, is the data.
Speaker 13 (40:36):
And the people.
Speaker 11 (40:37):
You know, training your teams to think about AI first
and how to bring AI into a business to add value,
so it could make an AGENC that could do make
autonomous decisions and be managed appropriately. The data foundations, so
the models don't hallucinate. All that has to be done
regardless of the technology that you choose. So that's where
(40:57):
I think the real area that we can add value
in helping our clients navigate both the frameworks, the governance,
the training of the people, all the change management, and
the data.
Speaker 13 (41:07):
All that still has to happen regardless.
Speaker 11 (41:09):
Of which model that you choose to use and the
foundations you build on.
Speaker 7 (41:13):
So the spend is going to still happen. Nobody's going
to put back.
Speaker 11 (41:17):
Yeah, I think it'll depend on what the use cases
and what the spend will be. So I think that
is yet to be determined, depending on the models that
our clients use. And many of our clients are using
large models, and many of our clients are using their
data and developing small models. But you know, I do
think this is a race that is continuing and we're
going to see this evolution and many more to come.
Speaker 5 (41:38):
Where do you see the actual money savings happening with
these companies that you work with? Is it from a
customer service perspective? The whole rise of the AI agent?
Where do companies where would our margins be helped?
Speaker 13 (41:54):
Yeah? So I think there's two things.
Speaker 11 (41:55):
You know, there's a whole site of productivity and efficiency.
Seeing that in development, you know, making our developers more
productive and more efficient, and we're seeing it in testing
of technology and applications. Absolutely, we're seeing that today. There's
also things like contact center where we're helping clients in
servicing and using AI to make the agent smarter and
(42:18):
delivering higher quality engagement. So there's lots of area where
we're seeing productivity and efficiency and the question is does
that translate into our clients being able to add more
higher value work to those or driving the costs down
in their business.
Speaker 13 (42:31):
And we're seeing both. You know, we launched just as I.
Speaker 11 (42:36):
You know, one example is whippro now, which is a
HR intelligent agent and we've put all of our HR
policies and procedures into this agent and it's serviced over
eight million queries to date at greater than ninety percent accuracy.
We've been able to reduce the number of of HR
employees to service those queries and to service those and
(42:59):
be able to reap purpose. So you can say that's
a great efficiency play, but it's also a great employee experience.
Our employees are able to get real time information, real
time insights into HR and be able to have a
better experience than maybe looking for documents in lots of
flou volders.
Speaker 3 (43:16):
Well, that's what I wanted to ask you. What was
the kind of satisfaction rate as I play around or
increasingly am you know, working with chats chatbots to deal
with service customer service issues. I mean, sometimes it's really
great and sometimes it's not. So I'm curious from your
internal team how did it go or what you guys
have learned in the process, because it's never perfect right
out of the gate.
Speaker 13 (43:36):
No, it isn't, and it takes time.
Speaker 11 (43:38):
In the early days, you know, the the the quality
wasn't as good as it is today, and the satisfaction
is really high. I don't have the specific numbers. I
know I've used it and it has been great. The
reality is it's not the chat bots, which is based
on rules. It's the it's an intelligence agent, so it
learns over time and we all know.
Speaker 13 (43:58):
That's the power of AI. AM that's what it a
great experience.
Speaker 11 (44:01):
So when something needs to be adjusted, it can be
and when there's feedback, it constantly is iterating, so it's
only getting better over time and becoming that that, you know,
the most intelligent HR agent it can be. So I
think overall it's the right direction in terms of creating
a great employee experience and enabling HR to do what
(44:21):
they should be doing and taking care of people and
not just answering simple questions. And I think that makes
it for a more interesting HR experience for that employee
as well.
Speaker 5 (44:31):
What about the administration and the role of the Trump
administration in this. We started the announcement of Stargate last week,
one hundred billion up to five hundred billion dollars of
investment from AI companies. What was the conversation happening around
this administration with regard to AI.
Speaker 13 (44:46):
I'll tell you.
Speaker 11 (44:47):
At Davos, there was optimism around the global economy and
the resilience as well as the US economy, and overall,
there was interest around what we're doing around AI as
well as regulatory policies, and I think overall there was
really just great optimism in Davos around the US economy.
Speaker 3 (45:08):
So in terms of kind of where we go from here,
you know you're in it. You guys are doing it
at your own company, you're working with companies consulting when
it comes to AI. You know this is your number
three right that this continues certainly to be an investment theme,
although taking a big hit in today's session, no doubt
about it. So top of mind that you think investors
(45:28):
should be watching out for. And just got about thirty
forty seconds here.
Speaker 11 (45:32):
Yeah, I see the investment in AI to continue and
I and you know, I think the speculations is going
to double in the next couple of years.
Speaker 13 (45:41):
I don't believe that test changed.
Speaker 11 (45:44):
Our clients are investing A and AI, and I think
today's announcements and what we saw today only emphasizes the
importance of.
Speaker 13 (45:53):
The innovation moving at pace.
Speaker 11 (45:55):
And I really do believe it shows that those who
invest now in bringing AI into and learning and experimenting
and scaling will be the market leaders. It's going to
disrupt every industry and that's what We're encouraging our clients
to do to lean in and you know, power their
organizations with AI. And that's why we've added you know,
(46:16):
whip Pro powered AI and we really believe us being
powered by AI will only help our clients be successful
and implementing in their own business.
Speaker 5 (46:24):
Susan Dad, CEO of America's over at the global consulting
firm whip Ro, joining us from New Jersey this afternoon.
Speaker 7 (46:35):
Macout you let me drive.
Speaker 12 (46:37):
Oh no, no, no, no, this is not a toy, Judge, Honey, please.
Speaker 11 (46:42):
I.
Speaker 3 (46:45):
Want to drive.
Speaker 4 (46:48):
It's a good question.
Speaker 2 (46:53):
This is the drive to the clothes that plungs for MEFIC.
Speaker 3 (46:58):
On Bloomberg Radio, all right, everybody got about eighteen minutes
left to end the Monday trade. You are listening and
watching Bloomberg Business with Carol Master along with Tim Stenovek
live here in our Bloomberg Interactive Broker studio. You heard
Charlie and Bill Maloney breaking it down. S ANDP down
about one point seven percent, the Nawstak one hundred down
the most when it comes to the index trade looking
about three point two percent decline here. I am curious
(47:21):
to see what Aaron Kennon has to say about all
of this. Co founder and CEO at Clear Harbor Asset Management,
they've got about one and a half billion in assets
under management. Joining us once again from Stanford, Connecticut. Aaron,
the story that we're all talking about deep seek, I
am curious.
Speaker 7 (47:37):
I know, you know, we're trying to put it into context, trying.
Speaker 3 (47:42):
Because it's not like the whole market is selling off
and everybody running for the exit door. So how do
you think about something like this?
Speaker 8 (47:50):
Yeah, thanks for having me back, Carol. I think at
the end of the day, we're seeing the evolution of
artificial intelligence in large language models. We're seeing what I
would call sort of the gradual commoditization of artificial intelligence,
and you know, less compute power and you know, less
GPU power, less electricity demand needed for a product that
(48:15):
is ninety eight percent as good as the best product
we have here in the United States is the story
of the day. And obviously the hyperscalers are under a
lot of pressure, as you mentioned at the break there
in Videos down seventeen eighteen percent. Broadcom is down seventeen
eighteen percent because they were the sort of hyped up
companies so to speak, that we're going to be the
(48:38):
beneficiaries of this AI demand. You have data center stocks
which are very much part of that ecosystem down big today.
You have sort of the cooling stocks that cool the
data centers down big today. But then you have other
parts of the technology landscape today that are interestingly doing
quite well, and they seem to be almost like the
beneficiaries of this commoditization of AI as I'm calling it,
(49:00):
which is that which is to say, if you remember
just a month or two or even a week ago,
it was how much is you know, Facebook, how much
are are Meta? How much are these other companies spending
on cap x And essentially that's to purchase the hyperscalers,
the Nvidia chips, the Broadcom chips. And now that narrative
is changing. And so you have software companies like you know,
(49:23):
Salesforce and work Day and Service now that are huge
beneficiaries of the implementation of AI into their software packages.
But now they're thinking this morning, well, I guess maybe
this this will cost us less, and those stocks are
in the green today.
Speaker 5 (49:38):
Yeah, that's that's interesting to hear. I'm wondering if you're
using this as an opportunity to buy or sell. Are
you changing asset allocation at all within your portfolios?
Speaker 8 (49:49):
Well, not doing a lot today, but happily it's challenged.
If you're an active manager in Vidius fifteen percent of
the Russell one thousand technology, you know if it's six
percent of the S and P five hundred. So even
if you're an active manager, and even if you own
these names that aren't doing well today, you have to
(50:10):
own more than within if your benchmarks the SMP, you
have to own more than six percent of Nvidia and
the SMP to say well, that's a real active bet, right,
So unless you're underweighted, and so no, I we we
feel reasonably good today. We have good broad diversification. I
think there's been a lot of concentration in this market.
(50:30):
We saw that in twenty twenty four, tim where if
you look at the S and P five hundred, almost
sixty five percent of the returns last year came from
ten names, of which many are the names we're talking
about right now. And you know to the extent that
there's a broadening out of the market advancement in twenty
twenty five, if we are up on the year, we
welcome that. You look at the equal weight S and
(50:51):
P five hundred today, it's only down one quarter of
one percent today, quite telling, So.
Speaker 3 (50:58):
Forgive me, did you so? Would you are you buying?
Would you be buying an end video? Would you buy
a broadcom? Because they've all of a sudden been whacked
in a big way. If you still believe in them
fundamentally and I'm not sure if you do or I'm
just curious.
Speaker 8 (51:13):
Yeah, we believe in growth opportunities within the technology segment.
We would also argue that there has been a significant
amount of passive dollars flooding into these names, driving them.
If you look at the top seven names of the
S and P five hundred, they're trading over thirty times
(51:33):
forward multiples. You look at the bottom four under ninety
three names trading at seventeen times. So do we think
they're quality companies?
Speaker 10 (51:40):
Yes?
Speaker 8 (51:41):
Do we think that some of them are not trading
at necessarily that the most attractive price point? Yes, and
we think we can be in the affirmative on both.
But we do think too that that doesn't necessarily mean
over the long run that dollars are going to be
accruing significantly away from these hyper scalers. But this broad
opportunity across technology. Even the utility landscape today is quite interesting.
(52:03):
Where this whole narrative around electricity demand, we've been hearing
it for weeks and months. Look at Constellation Energy today,
this is the deal.
Speaker 6 (52:10):
That Microsoft did right three Mile Island.
Speaker 8 (52:12):
That's down twenty percent today, yea.
Speaker 6 (52:17):
Down thirty percent today.
Speaker 8 (52:18):
Look at the water utilities today that no one wanted
to talk about last year. They're up five six seven
percent today. So it's really interesting. This rotation interesting?
Speaker 3 (52:26):
So interesting rotation? Is it an investible interesting rotation?
Speaker 8 (52:32):
Well, I mean, just look at multiples. I mean, are
we gonna Are we going We haven't contracted permitted a
nuclear build out since the nineteen seventies. The markets acting
as though we're going to have a dozen nuclear buildouts
contracted in twenty twenty five. It seems highly unlikely. I mean,
(52:52):
we do think that we're gonna have less regulation. But
even the announcement at the White House last week was
quite quite interesting. Where you know, if you look at
thee hundred billion dollars spend a year for four years,
actually more than that, it's five hundred billion over four
years that was announced to build out AI infrastructure. That
timing looks a little off right now, but to build
(53:12):
out AI infrastructure, the amount of electricity demand for those
data centers would be about one point seven gig a
lots per year based on the dollar spin that they're
talking about. That's about that's that's over. That's about it.
Actually it's two point seven excuse me, that's almost three
nuclear power plants a year just for that project. So
that we were getting I think over our skis in
(53:34):
the marketplace to some extent a.
Speaker 10 (53:37):
Short time.
Speaker 5 (53:38):
Okay, if we're getting over ski if we were getting
over skis now to continue the metaphor, where are we
on the on the slope?
Speaker 8 (53:45):
Well, I think there are plenty of opportunities in the market,
as I mentioned, if you look at forward multiples outside
of this sort of you know, hyper focused area of technology.
We've even in utilities as I mentioned, you know, the
water utilities, they have nice roe growth, they're training at
reasonable multiples. You look at the industrial segment of the market,
(54:07):
we're seeing a lot of opportunity across the board there.
If you look at you know, certain segments of the financials,
we think MNA activity is going to accelerate this year.
Private equity funds have in many cases reached the end
of their life in terms of the limited partnership duration
of ten years or more, and so we think that
(54:30):
these companies are going to need to be either brought
into the public market or sold in back into the
private market this year. Huge opportunities for banks, advisory firms,
companies that work on valuations of private equity. So you
have plenty of opportunity there too.
Speaker 7 (54:46):
All right, Aaron, thanks so much.
Speaker 3 (54:48):
Aeron Kennon He is co founder and CEO Clear Harvard
Asset Management, joining us from Stanford, Connecticut.
Speaker 2 (54:53):
This is the Bloomberg Business Week podcast, available on Apple, Spotify,
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