January 9, 2026 • 43 mins
Bloomberg’s Ed Ludlow discusses Meta’s latest energy deals for AI data centers that will make it the biggest buyer of nuclear power among its hyperscaler peers. Plus, MiniMax, one of China’s largest generative AI startups, goes public in Hong Kong. And, Snowflake CEO Sridhar Ramaswamy talks about the company’s plan to buy AI-powered observability platform Observe.
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Speaker 1 (00:02):
Bloomberg Audio Studios, podcasts, radio news.
Speaker 2 (00:08):
This is Bloomberg Tech coming up.
Speaker 3 (00:10):
Meta agrees to a series of electricity deals to power
data centers, making it the biggest fire of nuclear power
among the hyperscalers plus Minimax, one of China's largest generative
AI startups.
Speaker 2 (00:22):
Goes public in Hong Kong.
Speaker 3 (00:24):
For that means with China's AI ecosystem and Snowflake plans
to buy Observe, an AI powered observability platform. We're going
to discuss the move with Snowflake's c EO. Let's get
right to it and what's happening in the markets. Later
in the program, we're going to go big on Intel. Lipbutan,
Intel CEO has spent the last twenty four hours in Washington,
d C. In the White House with the President and
(00:46):
with Howard Lutnik, the Commerce Secretary. Glowing remarks from President
Trump about Litbutan's leadership of Intel, but also the progress
that the US government's made in taking a steak in
the chip maker.
Speaker 2 (00:57):
More to come.
Speaker 3 (00:58):
Then there's the big one investing in a multi gigawatt
deal with some big names in nuclear energy. Opkloat up
fourteen percent on that deal. Of course backed by some
outman district corps. Up thirteen percent, Meta up eight ten
to one percent. We said at the top of the program.
This puts them among the biggest energy buyers, among the hyperscalers,
and we remind ourselves Meta is not technically a hyperscaler.
(01:22):
That's get the blue most Riley Griffin details here really
important size of the deal, how many gigawatts, but also
the structure.
Speaker 2 (01:30):
Please.
Speaker 4 (01:31):
Yeah, So three different agreements and they actually are different
in form and functions. So this is about supporting up
to six point six gigawatts in nuclear energy, but it
is both about ensuring that existing nuclear power plants continue
to thrive and investing in future nuclear power. Meta's head
(01:51):
of global energy told me last night that they heard
that there's real concern about the amount of energy that's
out there. As you know ed, there's an insatiable demand
for energy, and this cements their low carbon play.
Speaker 3 (02:04):
I'll find this fascinating because while Meta is not a
hyperscale or a hyperscale of being a cloud computing company
that basically leases capacity, Meta is doing this on its
own behalf right. It has been aggressive in in securing
the supply of energy it needs for its own data centers,
which principally I use for training and inference of its
(02:25):
own activity in AI. What else has it done and
where does this bring them to date?
Speaker 4 (02:30):
Well, I want to note that you made a really
important important point there. Prometheus and Hyperion. These are two
of their biggest AI plays. Prometheus actually is in Ohio
and these agreements are in Ohio and Pennsylvania. So some
of this energy presumably is going to go to the
Prometheus data center cluster, which is one of their biggest plays.
But we're also seeing Meta turn with Hyperion to natural gas.
(02:54):
At least three natural gas plants are being fired up
just for that single facility, So it's not like nuclear
is the only strategy that Meta is employing here.
Speaker 3 (03:03):
We're going to get to the sort of available energy
sources around the world in a little bit. There is
an interesting point you co reported this with Will Wade,
who's just been really on top of the nuclear side
of the story. There does seem to be some anxiety
from the technology companies that the existing NUCLEME infrastructure that
does exist in America, limited as it may be, is
(03:25):
also at risk at being shut down. Is this kind
of future proofing a little bit.
Speaker 4 (03:29):
Absolutely, that is what I'm hearing from metas head of
Global Energy. They started back a December two years ago
and they were looking into what nuclear needed to keep going,
and they heard we need investment now into plants that
could potentially shutter. So this is a future proofing, as
you say.
Speaker 3 (03:46):
Bloomberg's Riley Griffin leading our coverage of Meta with a
must read, Thank you very much. Access to power has
been top of mind in AI. We spoke about that
with Nvidia CEO Jensenmong earlier this week.
Speaker 5 (03:56):
In order for our new industry to emerge, you need energy,
and so I think it's safe to say that we
wish we had more energy in the United States. Your
wis should have more energy. I think the world all
wish we have more energy, and so we have to
invest in all sorts of different forms of energy.
Speaker 2 (04:13):
Let's bring in Paul Meeks for more.
Speaker 3 (04:15):
He's managing director and head of Technology research of Freedom
Capital Markets. And when I was reading your research last night, Paul,
A little bit relieved coming up this morning when I
saw the Meta headline, because you're very focused on the
real terms footprint of data centers. That's what we're talking
about here. You heard Riley's reporting on the specifics of
(04:35):
what Meta has done to secure future capacity. How much
of a bottleneck is that to your mind right now?
Speaker 2 (04:42):
For this sector?
Speaker 6 (04:45):
It is absolutely critical of all the bottomnecks. It is
the most important. I like what Meta is doing here,
but folks need to realize that if you ramp up
nuclear capacity, we're not going to really see power generation
until twenty thirty earliest, maybe even not until twenty thirty two.
(05:08):
So what do we do for the next four to
six years? So the immediate draw is probably that gas.
But when I look at all of these companies and
we cover the AI hyperscalers and the neo clouds and
everybody adjacent to them, we are looking for their availability
(05:29):
for power, their capacity to find power, because it's not
a demand issue, it is a supply issue focused on
this particular metric.
Speaker 2 (05:41):
You know, pool.
Speaker 3 (05:42):
I played you just just some of the interview that
we conducted with Jensen Wong earlier this week, and when
I was sitting in front of him, you don't really
get any sense of anxiety from him, right Think about
the mechanics of how this transaction works and video brings
GPUs actually that's probably not fair. Increasingly they bring more
of the content of the server, but there is an
(06:05):
acknowledgment that something needs to change, principally in America. He
did go on to talk about the differences between Europe,
Asia and the United States and where we're sourcing energy.
Do you get a sense from your research that the
companies you cover acknowledge the severity of that deficit right now?
Speaker 6 (06:24):
So when they are public facing, particularly somebody like Jensen Wong,
who is essentially the spokesperson for the entire industry, they
have to exude optimism. However, behind the scenes, particularly when
I'm talking to companies about my financial models, which of
course the revenues and then the follow on cash flow
(06:45):
and earnings come from.
Speaker 7 (06:48):
Do you have the power?
Speaker 6 (06:50):
Yes, they are anxious, and I think they're actually very anxious.
Speaker 3 (06:56):
There will be people watching Bloomberg Tech that work at
Meta or in the AI industry. There will be Meta
investors watching this program, and some of these people may
never have heard of an outclow.
Speaker 2 (07:07):
Have you had to.
Speaker 3 (07:08):
Change the remit and breadth of your coverage if you
say I cover AI data center to include future sources
of electricity supply, Yeah.
Speaker 6 (07:19):
It's really interesting, ed that years ago, you know, nobody
in my line of work covering tech sector like I
have for decades, would be interested in any utility company.
It's the antithesis of tech. They are boring, regulated, slow
growth businesses. However, now they've come to the four and
of course these are not just your regular utilities, you know,
(07:40):
they're your new era utilities. But yes, if you are
a good analyst, you have to cover the entire supply chain,
the entire ecosystem. And because demand is so robust, we're
focusing on supply absolutely critical. And it's not just the power.
There are physical constraints here, like simply pouring the cement
(08:04):
to build the next data center, which can't be a bottleneck,
even though it sounds, you know, so old school in
a new school business. But yes, these are some factors
that are very, very interesting that people didn't even conceive
of a couple of years ago.
Speaker 3 (08:20):
Pol is there an adequate federal level framework regulation to
support the energy requirements of the AI industry in this country?
Speaker 6 (08:32):
You know, there is not. And here is my problem.
We are still suffering from a lack of solid regulation
for the Internet because even today in the US the
Internet is operating under nineteen ninety six legislation when Bill
Clinton was president, and so I'm hoping that we're not
too restrictive.
Speaker 1 (08:52):
Right.
Speaker 6 (08:53):
We need to embrace our entrepreneurial companies and give them
room to roll, but we need to have some guards
else on everything AI because what happened last time is
we end up abdicating the legislation to the EU because
we didn't have the will to do it ourselves. So
we missed that opportunity in the Internet. Here is the
(09:15):
next wave. We need to embrace it and at least
come up with some guardrails that are going to guide
all this because there are some important decisions on the
federal level to be made.
Speaker 3 (09:27):
In your research pro it's very interesting to see you
approach data center from the perspective of yes, you know,
energy supply, but also real estate. The reats right, and
what you want to ask you is away from the GPUs,
where are the frailties in that industry? Is it literally
the folks building the tin can around the outside of
(09:48):
the data center, the labor, the concrete.
Speaker 6 (09:52):
Yeah, we've seen some hit in short term revenues because
a couple of the number or a few of the
players have subcontractors. Now this is not them, this is
their subcontractors.
Speaker 7 (10:04):
That are delayed.
Speaker 6 (10:06):
What we call building a powered shell. So it's more
than a quandset hut that you might find the army in.
These powered shells are a little bit more sophisticated. But
one company I cover had a one hundred and fifty
million dollars revenue deferral from twenty five to twenty six
because at one of their forty one data centers someone
(10:28):
couldn't pour concrete because it was raining. And so yes,
all these things come into play, and it's interesting that
they may not necessarily be technical bottlenecks, but old school
physical including construction bottlenecks. In addition to the power.
Speaker 2 (10:45):
I just go back from Vegas.
Speaker 3 (10:46):
With all the attention on artificial intelligence in the digital world,
we have an industry that's getting hit by a rainstorm.
Pool meeks, buckets, unbelievable. It's great to have you on
Bloomberg Tech. A lot more to come and coming out
an exclusive interview with the co founder and COO of
Minimax after the company just went public in Hong Kong,
(11:07):
and that's the debut trade.
Speaker 2 (11:08):
And this is Bloomberg Tech.
Speaker 3 (11:23):
Minimax, one of China's largest generative AI startups, backed by
Ali Barber and Abadavi Sovereign Well Fund, is now public.
Shares surge in Hong Kong after an IPO that raised
six hundred and nineteen million dollars, closing up one hundred
and nine percent in its Friday debut trading. Bloomberg Stephen
Engel spoke exclusively with co founder and COO Yee Yun
(11:46):
about growth and expansion plans as Minimax faces hot AI
competition both locally and globally.
Speaker 8 (11:54):
We really focus out that capital efficiency caused the efficiency,
so we had always spent a round five hundred media
USC in the in total, probably only one or two
percent of the biggen suspending, So we did all the organization,
mad creativity innovations on.
Speaker 9 (12:11):
The h How do you compete though, if you're going
to go global, how do you compete with an open
AI or others that are throwing lots of capital at
their business?
Speaker 2 (12:22):
Is it viable and what is the.
Speaker 9 (12:23):
Technology gap looking like in the next few years.
Speaker 8 (12:26):
Actually, I don't think it's a competition. It's more about
all the top talents across all the world. They bring
the technology break through to the society, to the end users.
So you will see each models have pros and accounts,
so we focus more resources on building the models, building
the best product experience to a more and more uses
(12:48):
from all the world.
Speaker 4 (12:49):
To use it.
Speaker 9 (12:50):
We're hearing as well, the Chinese government might approve in
Vidia's H two hundred for China in this quarter. Perhaps
is that something you need to look at importing more
advanced accelerators for your training.
Speaker 1 (13:03):
And the like.
Speaker 8 (13:04):
I think in every industry with a really high growth
when the new technology comes here, so you will see
every startups, all the companies. This please resources comestring probably
chief constring computing constring is only one of the challenges.
So in the past you will see our model performers
and our product performers, so our resources is stable. We
(13:26):
can get access to all of them, so we focus
more on our R and D and foundation model. So
we just use whatever chiefs who make sense for us
at that specific stage.
Speaker 9 (13:37):
Is your goal to stay indigenously with your chips locally
made chips or would you buy nvidio chips as well?
Speaker 8 (13:46):
It doesn't matter what kinds of chiefs it is. It's
more about which chiefs can give us best ROI, which
can help us to achieve our mission to make the
best technology too accessible to all of the users across
the world.
Speaker 9 (14:00):
So when does the emphasis turn from efficiency to profitability
and also getting that steady revenue growth that will then
justify a higher stock price valuation.
Speaker 8 (14:12):
So we put loss of R and D resources and
innovations on the efficiency part. You will see our API
we have the enterprise business and you will see the
gross profit margin of our API is more than sixty
five percent, which is probably already one of the highest globally.
So we focus more on make the best technology and
(14:32):
the best the user experience that people would love to
pay for the best performers models for their use cases.
Speaker 9 (14:39):
You've also come out of a price war essentially a
race to the bottom some have called, because of you're
trying to keep costs down and you want to survive
as well. There was a battle of survival and you
have been one of the survivors. But at the same time,
the startups are not the only ones. The big players
Ali Baba, by Dads, tens and others. How do you
(15:02):
compete with them at a low cost basis?
Speaker 8 (15:05):
Actually it's not. I don't think that's a press word.
It's more about the performers the competition, So you need
to make your model best. And the people I mean
and the user are interpress customers. They don't choose your
model because of its cheap or expensive. It's more about
its performers. So that's the key. As you said, I
(15:26):
think it's not about the competition between like all these
big chenz, but it's more about some of them. They
are like our cloud providers and some of their products
you see our models, So it's more about the collaborations.
All this company brings the foundation models to all the world.
Speaker 3 (15:44):
Many Max co founder and COO Yaun speaking exclusively with
Bloomberg Steven Engel. Public listings in Hong Kong are hot
right now. Chinese industrial robot maker in Events is now
also considering a second listing in Hong Kong, according to sources.
Let's get out to Bloomberg Executive Tech editor Peter Elstrom.
Speaker 2 (16:02):
To discuss this.
Speaker 3 (16:02):
But also like this growing trend of more of China's
sort of post chat gbtai firms going public. The team
that you lead out in Asia busy right now. In
Events's case, what are the details in our reporting that
we need to know about.
Speaker 10 (16:18):
Yeah, there are a lot of these IPOs that we're seeing,
and we're seeing a much more forward move into the
public markets for a bunch of these companies and events
has already gone public in the mainland and Shenjen now
it's looking at an IPO in Hong Kong.
Speaker 11 (16:32):
Two.
Speaker 10 (16:32):
That's partly a reflection of how hot demand is from
investors for these kinds of companies. When you're talking about
Minimax in particular, they went public, as you mentioned, their
shares more than doubled in the debut. The founder of
the company is very fascinating. These are some people called
them the AI tigers, some people the AI dragons. But
these are startups that really have very very different strategies
(16:53):
for how they're approaching the market. Compared with some of
the US competitors, Like in open Ai, they tend to
be much lower cost models. They tend to be much
more aggressive about implementing the technology with their customers, with
corporate customers, and giving them very low cost, very low,
very efficient models that they can use and they can
actually deploy more quickly than some of the US counterparts.
Speaker 3 (17:13):
PETE in the world of technology or in financial market's
like a term like an AI tiger or AI dragon.
Speaker 2 (17:18):
You know, it's kind of commonplace. We bandy it around.
Speaker 3 (17:21):
But for those watching Bloomberg Tech that are saying, what
are you talking about? How do we define the AI tiger?
What are we talking about here?
Speaker 10 (17:28):
Well, we're talking about a whole series of companies coming
out of China. In Stevens interview with the Minimax COO,
they talked about the competition there. We've of course heard
a lot about Deep Seek and how good their model is,
how technically good it is, but also how low cost
it is. Behind Deep Seek, you have a whole bunch
of other companies like Minimax, like Jipou, which just went
(17:48):
public on Thursday. So yeah, the IPO of Geepoo on Thursday,
mini Max on Friday investors showed a lot of demand
for those shares. And what these companies have been able
to show is that with a very low cost model,
they're out there in the market competing. It's not clear
that they're going to be able to compete directly with
Open AI or Anthropic, but they have very innovative models.
I mean, first of all, the US models are not
(18:09):
going to be let into the China market. But these
companies are also going out very aggressively and competing in
some other parts of the world. We've written about how
much traction Deep Seek is getting in Africa in particular,
because their companies are sensitive to costs. They're sensitive to
how much power, how much computer resources they need to
be able to deploy these models. So they are having
some successes. We're going to see a lot of competitive
(18:31):
clashes in the months ahead.
Speaker 2 (18:33):
Bloomberg's executive editive for Tech, Peter Alstrom. Great to catch
up with you, Thank you so much. Now coming up
on the.
Speaker 3 (18:38):
Program, Love Musks Grock image generation tool faces backlash after
reports that's generated thousands of undressed women and children.
Speaker 2 (18:48):
Go more on that data. Next, this is Bloomberg Tech.
Speaker 3 (19:00):
Elon Musk's AI startup Xai is burning cash quickly. The
company spent almost eight billion dollars in the first nine
months of the year. That's according to internal docs that
Bloomberg's viewed. Though revenue has nearly doubled quarter over quarter
to one hundred and seven million dollars, Xai's losses have
been mounting on costs to build data centers, recruit talent
(19:22):
developed software and to build AI that is self sufficient,
and according to Bloomberg's reporting, the plan is to use
that AI to eventually power Tesla's humanoid.
Speaker 2 (19:33):
Robots in the Optimus program.
Speaker 3 (19:35):
Right Sticking with XAI, the company has limited access to
Grock's image generation tool for most users, following widespread criticism
that the feature was producing thousands of explicit images of
women and children. Bloomberg reporter Cecilia Deannastasio broke, the story
has been tracking the developments, Cecilia, that we just summarized
(19:58):
the issue, right think, let's start with the methodology, how
we went about looking at the data, how we got
the data, and we'll go from that.
Speaker 1 (20:07):
Thank you for having me. Bloomberg worked as a researcher
who scraped thousands of images produced by groc and published
to the platform X between the period January fifth and
January sixth. The researcher analyzes images to determine what percent
of them were sexualized and neudifying, and found that every
hour during that twenty four hour period, X was publishing
about six thousand, seven hundred images identified as such, and
(20:31):
just for a comparison, websites that are dedafied dedicated to
publishing deep faked images AI generated images of women who
are sexualized neudified. Those top five websites out there published
together eighty images per hour. So GROC is one of
the biggest deep fake producers on the Internet today.
Speaker 2 (20:51):
Where are these images showing up?
Speaker 3 (20:53):
You know, to the uninitiated people may not know the
sort of interconnects between XAI the AI company, and x
the social media platform, for example, but they are now
kind of one entity as they combine last year.
Speaker 1 (21:08):
Well, that connection is exactly why x has become one
of the biggest deep fake websites on the internet. Anybody
can well not anybody now, now you have to pay
to do this, But over the last couple of days,
anybody could just at rock on the X platform and say,
put this woman in a bikini under an image that
a woman had post on the internet. And a lot
of women women primarily are the victims of this, took
(21:30):
to complaining to GROC directly and arguing with GROC in
their comments.
Speaker 7 (21:34):
GROC would apologize for posting.
Speaker 1 (21:36):
These images, but then continue posting them and not take
down Many of the images that the women felt were violating.
Speaker 3 (21:42):
Succeed That did X or XAI respond to our reporting,
engage with us on it.
Speaker 1 (21:49):
X has not responded to our numerous requests for comment
over the last couple of days. Elon Musk himself, in
a reply to a post on X said anybody using
groc to make illegal con tent will suffer the same
consequences as if they upload a legal content, and Musk
there was referring to allegations we believe of child sexual
abuse material that's been posted to X using the croc app.
Speaker 3 (22:12):
Okay, Bloomberg's the CID Danna Slasio important reporting.
Speaker 2 (22:15):
Read the story on the Bloomberg terminal on bloombuw dot com.
Thank you.
Speaker 3 (22:19):
Now, coming up from the program, we're going to speak
with Snowflake CEO Shrida Ramaswami. Is the company enters into
an agreement to buy AI powered platform observe. We'll get
his observations on that piece of M and A that's
coming up next. You're halfway through the program, and this
is Bloomberg Tech. Welcome back to Bloomberg Tech. I've been
(22:51):
using the power of my Bloomberg terminal. It's been a
long week with cs and Las Vegas. The power of
my brain is dwindling. But it tells me that Apple
is down for an eighth straight session, which matches the
run of declines that Apple saw in May of twenty
twenty five.
Speaker 2 (23:06):
Now using more of the power of the Bloomberg terminal.
Speaker 3 (23:11):
If Apple was full for a ninth day, we think
that would be the longest run of decline since the
early nineties. And obviously we are only nine days into
twenty twenty six. But so far year to date, this
is a stock that's down five and a half percent.
You saw the letter from Tim Cook to shareholders talking
up the company's progress of late and last year, but
(23:32):
right now that stock heading down and will continue to
track it. We had some M and A in the
last twenty four hours, but it's actually in the AI
and software space. Snowflake has agreed to buy Observe, an
observability platform and AI powered observability platform. Observability something that's
come up a lot recently, particularly in the context of AGENTICAI.
(23:53):
When I've been around the table, particularly on the engineering side.
Why this piece of M and A? Why now that's
sorts of Snowflake CEO Treda Ramaswami. Those are the reasonable questions,
right SHREDA I do want to get to defining observability
and why it's important.
Speaker 2 (24:10):
But it's an interesting deal. Why do you do it?
Speaker 12 (24:14):
Hey?
Speaker 7 (24:14):
Great to see you.
Speaker 12 (24:15):
Snowflake's acquisition of Observe is a game changer for our customers.
As you pointed out, observability is basically looking at applications, websites,
AIA agents to make sure that they are functioning properly.
Speaker 7 (24:28):
It's a diverse and messy problem. It's a big data problem.
Speaker 12 (24:32):
And because observer is built right on top of Snowflake,
they are able to use our very efficient storage as
well as computer platform to help customers find problems ten
times faster, often at three to four x less cost.
Take a company like Top Golf, it's a customer of
(24:52):
a Observe. I go to Top Golf all the time
with my team, not much of a golfer, so I'm
playing an angry Bird's game or something like that. Top
Golf used to struggle when these games went down because
they collected everything in a central place but could not
identify that a particular booth had problems. They're able to
do that with Observe in a matter of a few seconds,
(25:13):
send out a tech team to go fix that problem
and have happy customers.
Speaker 7 (25:17):
That's the power of this acquisition.
Speaker 12 (25:20):
Increasingly, capabilities like observability are going to be a core
part of a platform like Snowflake. And we have great
customers folks like Barclays, Capital One, Commonwealth Bank of America,
and we're super excited to bring this to over ten
thousand plus customers on Snowflake SHREDA.
Speaker 3 (25:40):
Let's get it out the way if we can. The
report saw that it's about a billion dollar deal. What
was the structure of the deal and the financials on it?
Speaker 2 (25:47):
Please?
Speaker 12 (25:49):
We can comment on the structure of the deal it is,
you know, some of it will come out in the
some of it will come out in the filing.
Speaker 3 (26:00):
Signal that there might be some more pieces of M
and A, particularly on that layer that you sit on
right you know, as you know very well you were
there on Monday at the video event Jensen talks about
the five layer cake and one of the layers you occupy.
But as observability evidence is, there might be pieces of
competency missing. How are you going to use M and
(26:21):
A to plug those gaps.
Speaker 12 (26:24):
We've been pretty open that we want to be an
end to end data platform for our customers from the moment.
Data is barn when you interact with an application, for
example two, bringing it in for analysis, analyzing it, and
then acting on it increasingly with AI agents. We've been
systematically going through this process of both acquiring customers and
(26:47):
building up.
Speaker 7 (26:48):
Functionality from within.
Speaker 12 (26:51):
Things like observability or data clean rooms are adjacent functionality
that sit on top of a data layer. You will
continue to be super act about both spinning up new
projects internally and acquiring companies. I think the environment is
right for that, and honestly, our customers want that because
they're spending entirely too much time just stitching things together,
(27:13):
and we make it seamless and easy to use for that.
Speaker 2 (27:16):
How competitive is that m and a environment right now?
Speaker 3 (27:19):
Because when I look at Observe and what it's offered, you,
you know, the analysts looked at that deal and said
completely logical that Snowflake would do it. But one would
imagine that there would be others in the market for
a name like Observe as well.
Speaker 2 (27:34):
Well.
Speaker 12 (27:34):
There are many things that we're going for this particular deal.
As I said earlier, Observer is built on top of Snowflake,
which means that we didn't have to deal with a
long integration cycle. The products are super tight. We've been
collaborating closely with the team as partners for a very
long time. I've actually gone and visited the Observed team
(27:56):
multiple times in their location in San Mateo. We felt
like this was a natural extension of who we were
as a platform, and we think that Observed, by using
both their technical capabilities and now also being part of Snowflake,
can offer an incredibly cost competitive solution. Cost has been
(28:17):
a big factor in the world of observability, especially with
things like AI agents, which are complicated pieces of software
that generate enormous amounts of essentially telemetry information.
Speaker 7 (28:28):
We think this is a good combination that's.
Speaker 3 (28:31):
Worth some academic debate, you know, should I'm not a
computer scientist or an engineer, right, so so take that
into account. But the thing that we argue about with
a truly autonomous AI agent is that it's exactly that
it is supposed to act. With autonomy and observability raises
the question of if a human is required at some
(28:53):
point in the process to check.
Speaker 2 (28:56):
In, what's your point?
Speaker 12 (28:58):
You know, well, it becomes a matter of how many
people you need in order to accomplish a problem. So
I live and breathe agent Kai. I mean, I really
mean that I use these products every single day. And
the leverage that you get is the game changer. Used
to be that a support ticket would come and a
(29:18):
person had to go read the text of what that
case was, copy and paste that text into multiple tools,
figure out what is going on, and then perhaps send
a Slack message over to somebody in order to answer
a problem.
Speaker 7 (29:30):
A lot of this, as you know, is low value work.
Speaker 12 (29:33):
Copying information from one screen or one app to another
is just tedious, it's no fun. I think the power
here with Agentic systems is going to be all that
boring stuff is going to be automated, so that when
a problem comes in, you go reach out to the
ten tools that you need to collect information from, you
analyze it, and then you show that somebody to that
(29:54):
person who decides what action to take.
Speaker 7 (29:57):
But furthermore, if they have to go write.
Speaker 12 (29:59):
Some custom gode to solve a new problem, they'll do
it two three times and turn that into a skill
that can be used by everybody else. I think it
leverages people enormously. I can tell you again from personal
experience that I can get stuff done in a matter
of a couple of hours on top of Snowflake building
things that would honestly have taken me two to three
weeks just last year to get done.
Speaker 3 (30:21):
That's the game changer that's here treat us. Snowflake rose
forty two percent last year. What are the goals that
you're holding you and the team to for twenty twenty
six and the things that you want to achieve this
year in AI?
Speaker 12 (30:37):
As you know ed, it's important to focus on the
things that you can control. What we're super excited for
twenty twenty six is making agent ki.
Speaker 7 (30:47):
Come alive for all our customers.
Speaker 12 (30:50):
Snowflake Intelligence is our agentic data product and it's been
a game changer again for me to do things like
do research on customers before I meet with them. This
is the fastest product in terms of customer adoption and
revenue in Snowflake's history. We want to make sure that
we drive adoption of these products, and in turn, what
(31:13):
this does is it enhances and makes the power of
data more and more visible to future customers. I expect
this AI to be a strong pull that makes data
modernization much much more relevant part every customer and future
customer of Snowflake.
Speaker 3 (31:31):
It is really that in and yang that I'm super
excited about. We started the week together in Las Vegas
at the Nvidia keynote. We end the week together talking
about the roadback from part four the Snowflake. Snowfake CEO
Shreeta Ramaswami. Great to have you back on Bloomberg Tech.
Speaker 2 (31:45):
Thank you.
Speaker 3 (31:45):
Now coming up, we're going to take a look at
the state of media mergers as one of brows sticks
with its buyout by Netflix and it's trying to shake
off that paramount takeover.
Speaker 2 (31:55):
We have the details. Next, this is Bloomberg Tech.
Speaker 3 (32:05):
Lairs of Netflix have tumbled nearly twenty eight percent since October,
but the streaming giant stock still appears to be too
expensive to many investors. Here of more is Bloomberg Stock Reporter,
All Things Terminal, authoring Squawk Police Morantz.
Speaker 2 (32:20):
This is a really important write up.
Speaker 3 (32:22):
Right there is so much hype and a lot of
headlines around what's happening with Warner Brothers Discovery.
Speaker 2 (32:27):
And you do what you needed it.
Speaker 3 (32:29):
You go back to basics, look at the fundamentals, look
at the stock to must read on the Bloomberg Tamila
dot com. But just I guess give us the top
line of the reporting.
Speaker 13 (32:37):
The top line is that this stock has really plunged
since investors started questioning whether this deal was a good
idea or not.
Speaker 7 (32:45):
You have questions about cost, You have integration risk as.
Speaker 13 (32:49):
Netflix doesn't have much experienced swallowing large deals, and you
also have a big regulatory fight that's looming. So there's
not a lot of extreme enthusiasm about the stock right now.
Speaker 7 (33:04):
In fact, it's down.
Speaker 13 (33:05):
You can see it's down about two percent today on
an update for the S.
Speaker 7 (33:08):
And P five hundred.
Speaker 3 (33:10):
The people you speak to it in the piece, you know,
one of the anecdotes is like Netflix is not screaming
by right now. Right But you also, I guess, look
at multiples, current multiples and historic multiples and compare them.
Speaker 2 (33:22):
What would that tell us?
Speaker 7 (33:24):
So there are various different kinds of multiples.
Speaker 13 (33:27):
But if you look at a basic price to earnings ratio,
the stock is not expensive historically, but Nora is it
very cheap.
Speaker 7 (33:36):
It's training a.
Speaker 13 (33:37):
Bit below its historic norm, but not enough to really
grab people.
Speaker 3 (33:44):
Bloomberg's police morans is awesome and it's been great to
have you back on bloombog take this Friday.
Speaker 2 (33:49):
Thank you very much. I want to get deep. You're welcome.
Let's get deeper into that deal.
Speaker 3 (33:54):
Part the future of streaming the Warner Brothers Discovery Saga
and then the two bids Matthew Dolgan, morning Star Senior
around equity and this covering communication services.
Speaker 2 (34:03):
Felice did a good job right going over the stock.
Speaker 3 (34:06):
But there's a piece of the deal that I asked
the team to find someone to dig in with us on,
which is do we value the cable networks part of
Warner Brothers Discovery at zero?
Speaker 2 (34:19):
Which paramount?
Speaker 3 (34:20):
When it reaffirmed it's thirty dollars a share bid came
out with your take on that.
Speaker 14 (34:25):
No, we don't think it should be valued at zero. However, well,
first of all, there is a risk that it could be.
We don't think that that's right. But this is going
to be a very heavily debt laiden company and that
leads to more risk, and so it's possible that zero
it would be in the future. We don't think that's
the most likely thing, but there is question of whether
it's worth two dollars a share or three dollars a
(34:47):
share or more and that matters because that is what's
making up the difference between what Netflix offered for the
portion of Warner Brothers Discovery that it wants versus what
Paramount offered for the your company. And so there are
a few different moving parts as you compare the deals,
which are not apples to apples. But it doesn't have
to be zero. If it's one dollar, like Paramount has
(35:10):
said previously, and this week with versants trading, that adds
another potential new data point, but it can be definitely
less than what the thirty is combined.
Speaker 3 (35:21):
So I'm just going to recap for the Bloomberg Tech audience.
Here's where we stand. Netflix has offered twenty dollars twenty
seven dollars a share for the streaming and the studios
and would plan to spin out the legacy cable networks.
And as we've said for five days in a row
on Bloomberg Tech, Paramounts Guidance want the whole enchilada, all
of it, but at thirty dollars a share, saying that
(35:42):
they assume a zero dollar value for that cable network.
You're covering the space, and you're covering these names, and
you're covering the deal. It's actually a very reasonable question
of what happens next. Because Warner Brothers board sent a
letter reject the Paramount offer and explained why. The next
(36:03):
day Paramounts guidence reaffirm that offer. We just continue in
that cycle.
Speaker 2 (36:08):
Well, we continue in that cycle for a little bit.
Speaker 14 (36:10):
Yes, January twenty first is a critical date that we
should circle on our calendars. That's when the tender offer
for the Warner Brothers Discovery shares by Paramount is currently
set to expire. So we'll see what happens at that point.
It doesn't appear that right now Paramount is likely to
get a sufficient number of shares by that date, but
(36:31):
they can extend it, extend the date, and they can
also well at any time. But that's when we would
expect potentially they would look at increasing their offer to
beyond thirty dollars a share. And so, yes, we do
kind of wait and see the next development. I don't
really expect anything until close to the twenty first as
far as new information. But at this point we'll see
(36:52):
where Paramount is on the shares that are being tendered,
and then the ball is kind of it's kind of
in its court as far as whether it wants to
do something else in the interim before later this spring
or summer, when Warner Brothers Discovery shareholders are likely to vote,
and that Netflix deal that the Warner board has recommended.
Speaker 3 (37:13):
We spend a lot of time this week talking about
the Warner Brothers Discovery rationale for rejecting Paramoun's guide on
so we included debt. It included a discussion either negative
or positive about Larry Allison being the bank stop on
the deal, and it talks about the restrictive covenants on
Warner Brothers not being able to make major investments what
(37:33):
in this interim period. But the question actually I have
is who would get the most out of those assets HBO, Max,
the catalog and then the studios, Like which company would
be better at getting them out into the real world
to your mind?
Speaker 14 (37:48):
Well, we think Paramount is the company that I guess
needs them more and probably would benefit from them more.
As far as getting them out into the world, that well,
arguably would be more Netflix a side with the business
they already have in place in the streaming service and
subscribers they already have in place. But if you're looking
from a business and an operating point of view, we
(38:11):
think Netflix has far less to gain as it does
that than Paramount would, which really needs the scale and
has I think a better combined type of offering, whereas
Netflix incrementally is sure it adds quite a bit to
it as far as incrementally on how much more revenue
that bring in, whether they're cannibalizing some of the profits
(38:31):
that Warner takes in with some of its licensing. The
reasons why we think that from a business standpoint, Netflix
doesn't benefit quite as much as Paramount would. That's of
course a maybe different question than what the consuming public
and how they benefit from the content and the availability
and the pricing for that.
Speaker 2 (38:48):
It's out there.
Speaker 3 (38:50):
You heard Felice's reporting on the stock why very quickly
we just have thirty seconds? Has that sentiment with Netflix
soured since the deal first kind of got announced.
Speaker 14 (39:02):
As far as the deal goes, I think there's been
some fear that Netflix would even pay more. There's also
some fear they've overpaid with what they've agreed to already,
so that may not be worth it. I also think
it's maybe just brought to light some things that we
had been thinking about for some time, even apart from
what's going on with Warner, which is the growth is
(39:22):
set to slow at Netflix, and therefore the multiples that
it had historically aren't necessarily justified today. And so if
it is at lower motiles now, which it certainly is
where compared where it's been historically, that's probably justified. Being
the growth outlook now versus in the past.
Speaker 2 (39:37):
We got to leave it there.
Speaker 3 (39:38):
But that brings us a nicey full circle to what
police was talking about at the start of the block.
Speaker 2 (39:41):
Matthew Dog in the morning, so thank you very much.
Speaker 3 (39:43):
Now coming up, Intel CEO was at the White House
to deliver a progress report on its activities. The US
government is its big shareholder that it's being accounting to.
Bit more on that next, as the Bloomberg Tech for
Talking Tech first up, Vodafone Idea is considering raising debt
(40:08):
financing to accelerate growth.
Speaker 2 (40:10):
That's according to sources.
Speaker 3 (40:11):
This comes after Delhi decided to cap annual payouts for
past spectrum fees, forerring a lifeline to the country's third
place carrier that's out in India. Plus compensation for Apple
CEO Tim Cook held steady at a cool seventy four
million dollars last year. Just three million of that comes
from salary, though the rest is in the form of
(40:31):
stock awards. You may remember a few years ago Cook
was criticized for pay packages close to one hundred million
dollars apiece, prompting him to request a compensation reduction, and
TSMC provided an upbeat sales forecast. The company reported a
roughly twenty percent rise in the December quarter revenues based
on calculations off monthly figures. The company reports full quarterly
(40:53):
earnings next week. All this coming after chip makers projected
optimism for AI demand at cs this week. Now, sticking
with Chips, shares of Intel up today in a big way.
Of the company's CEO delivered a progress report on its
company's U line of processors. At the White House, Libutan
met with President Trump and Commerce Secretary Howard Lutnik. After
(41:14):
the meeting, Trump praised Intel and said the government was
proud to be a shareholder.
Speaker 2 (41:20):
For more.
Speaker 3 (41:20):
Let's get out to Bloomberg's Ian King, who of course
leads our coverage of Chips. Actually, where I wanted to
start in is the President in his post talked about
the result of the government's investment in Intel, yielding I
think said tens of billions of dollars for the American people.
It's important probably to do the math on what the
actual return would be at this stage.
Speaker 2 (41:41):
Please.
Speaker 11 (41:43):
Yeah, no, I mean, as taxpayers, we own currently about
eleven billion dollars worth of Intel stock, and that's a
nice return, roughly twice what we owned when we made
the investment as a nation last year, and not in
the tens of billions. For that to happen, obviously Intel's
(42:03):
share price would have to go up a lot more,
and or some ex extra kind of arrangements that exists
would have to be bigger.
Speaker 3 (42:14):
All the same that there has been some stock performance
here since lit Bhutan kind of had this improvement in
relationship with the president. What do we know about yesterday's
meeting and kind of where Intel's focus right now in
what it's trying to tell the US government.
Speaker 11 (42:30):
Yeah, I mean, you know, the fact that he's in
the White House is important because that is basically drawing
attention to the fact that this investment that we saw
last year from the US government from in Nvidia, from
SoftBank has really stabilized Intel's kind of balance sheet, and
so it's in a much stronger position than it was.
(42:50):
But where we are and where we really need to
be is to have much better operations and much better
performance from the company, and that is going to take
new products. You and I were at CES this week
and we saw Intel come out and say, hey, here
are our new chips. These are the ones we promised.
These are the ones that they are going to deliver. Obviously,
three or four days into that launch, we don't know
how well they're going to do yet, but at least
(43:12):
in terms of the specs, way better than the position
that Intel has been in.
Speaker 3 (43:17):
And again a large portion of the government's ownership of
Intel is contingent on performance of those goals. Bloomberg Z
and King, Happy Friday to you and thank you very much.
That does it for this edition of Bloomberg Tech in
what's been a monster week. Frankly, just back from Las
Vegas and see yes and the headlines keep coming, particularly
in the world of AI. Great place to recap the show,
(43:37):
the week, the interviews and the reporting is on the podcast.
You know where to find it online, Apple, Spotify, iHeart
and all the Bloomberg platforms.
Speaker 2 (43:44):
Happy Friday. This is Bloomberg
Bloomberg Audio Studios, podcasts, radio news.
Speaker 2 (00:08):
This is Bloomberg Tech coming up.
Speaker 3 (00:10):
Meta agrees to a series of electricity deals to power
data centers, making it the biggest fire of nuclear power
among the hyperscalers plus Minimax, one of China's largest generative
AI startups.
Speaker 2 (00:22):
Goes public in Hong Kong.
Speaker 3 (00:24):
For that means with China's AI ecosystem and Snowflake plans
to buy Observe, an AI powered observability platform. We're going
to discuss the move with Snowflake's c EO. Let's get
right to it and what's happening in the markets. Later
in the program, we're going to go big on Intel. Lipbutan,
Intel CEO has spent the last twenty four hours in Washington,
d C. In the White House with the President and
(00:46):
with Howard Lutnik, the Commerce Secretary. Glowing remarks from President
Trump about Litbutan's leadership of Intel, but also the progress
that the US government's made in taking a steak in
the chip maker.
Speaker 2 (00:57):
More to come.
Speaker 3 (00:58):
Then there's the big one investing in a multi gigawatt
deal with some big names in nuclear energy. Opkloat up
fourteen percent on that deal. Of course backed by some
outman district corps. Up thirteen percent, Meta up eight ten
to one percent. We said at the top of the program.
This puts them among the biggest energy buyers, among the hyperscalers,
and we remind ourselves Meta is not technically a hyperscaler.
(01:22):
That's get the blue most Riley Griffin details here really
important size of the deal, how many gigawatts, but also
the structure.
Speaker 2 (01:30):
Please.
Speaker 4 (01:31):
Yeah, So three different agreements and they actually are different
in form and functions. So this is about supporting up
to six point six gigawatts in nuclear energy, but it
is both about ensuring that existing nuclear power plants continue
to thrive and investing in future nuclear power. Meta's head
(01:51):
of global energy told me last night that they heard
that there's real concern about the amount of energy that's
out there. As you know ed, there's an insatiable demand
for energy, and this cements their low carbon play.
Speaker 3 (02:04):
I'll find this fascinating because while Meta is not a
hyperscale or a hyperscale of being a cloud computing company
that basically leases capacity, Meta is doing this on its
own behalf right. It has been aggressive in in securing
the supply of energy it needs for its own data centers,
which principally I use for training and inference of its
(02:25):
own activity in AI. What else has it done and
where does this bring them to date?
Speaker 4 (02:30):
Well, I want to note that you made a really
important important point there. Prometheus and Hyperion. These are two
of their biggest AI plays. Prometheus actually is in Ohio
and these agreements are in Ohio and Pennsylvania. So some
of this energy presumably is going to go to the
Prometheus data center cluster, which is one of their biggest plays.
But we're also seeing Meta turn with Hyperion to natural gas.
(02:54):
At least three natural gas plants are being fired up
just for that single facility, So it's not like nuclear
is the only strategy that Meta is employing here.
Speaker 3 (03:03):
We're going to get to the sort of available energy
sources around the world in a little bit. There is
an interesting point you co reported this with Will Wade,
who's just been really on top of the nuclear side
of the story. There does seem to be some anxiety
from the technology companies that the existing NUCLEME infrastructure that
does exist in America, limited as it may be, is
(03:25):
also at risk at being shut down. Is this kind
of future proofing a little bit.
Speaker 4 (03:29):
Absolutely, that is what I'm hearing from metas head of
Global Energy. They started back a December two years ago
and they were looking into what nuclear needed to keep going,
and they heard we need investment now into plants that
could potentially shutter. So this is a future proofing, as
you say.
Speaker 3 (03:46):
Bloomberg's Riley Griffin leading our coverage of Meta with a
must read, Thank you very much. Access to power has
been top of mind in AI. We spoke about that
with Nvidia CEO Jensenmong earlier this week.
Speaker 5 (03:56):
In order for our new industry to emerge, you need energy,
and so I think it's safe to say that we
wish we had more energy in the United States. Your
wis should have more energy. I think the world all
wish we have more energy, and so we have to
invest in all sorts of different forms of energy.
Speaker 2 (04:13):
Let's bring in Paul Meeks for more.
Speaker 3 (04:15):
He's managing director and head of Technology research of Freedom
Capital Markets. And when I was reading your research last night, Paul,
A little bit relieved coming up this morning when I
saw the Meta headline, because you're very focused on the
real terms footprint of data centers. That's what we're talking
about here. You heard Riley's reporting on the specifics of
(04:35):
what Meta has done to secure future capacity. How much
of a bottleneck is that to your mind right now?
Speaker 2 (04:42):
For this sector?
Speaker 6 (04:45):
It is absolutely critical of all the bottomnecks. It is
the most important. I like what Meta is doing here,
but folks need to realize that if you ramp up
nuclear capacity, we're not going to really see power generation
until twenty thirty earliest, maybe even not until twenty thirty two.
(05:08):
So what do we do for the next four to
six years? So the immediate draw is probably that gas.
But when I look at all of these companies and
we cover the AI hyperscalers and the neo clouds and
everybody adjacent to them, we are looking for their availability
(05:29):
for power, their capacity to find power, because it's not
a demand issue, it is a supply issue focused on
this particular metric.
Speaker 2 (05:41):
You know, pool.
Speaker 3 (05:42):
I played you just just some of the interview that
we conducted with Jensen Wong earlier this week, and when
I was sitting in front of him, you don't really
get any sense of anxiety from him, right Think about
the mechanics of how this transaction works and video brings
GPUs actually that's probably not fair. Increasingly they bring more
of the content of the server, but there is an
(06:05):
acknowledgment that something needs to change, principally in America. He
did go on to talk about the differences between Europe,
Asia and the United States and where we're sourcing energy.
Do you get a sense from your research that the
companies you cover acknowledge the severity of that deficit right now?
Speaker 6 (06:24):
So when they are public facing, particularly somebody like Jensen Wong,
who is essentially the spokesperson for the entire industry, they
have to exude optimism. However, behind the scenes, particularly when
I'm talking to companies about my financial models, which of
course the revenues and then the follow on cash flow
(06:45):
and earnings come from.
Speaker 7 (06:48):
Do you have the power?
Speaker 6 (06:50):
Yes, they are anxious, and I think they're actually very anxious.
Speaker 3 (06:56):
There will be people watching Bloomberg Tech that work at
Meta or in the AI industry. There will be Meta
investors watching this program, and some of these people may
never have heard of an outclow.
Speaker 2 (07:07):
Have you had to.
Speaker 3 (07:08):
Change the remit and breadth of your coverage if you
say I cover AI data center to include future sources
of electricity supply, Yeah.
Speaker 6 (07:19):
It's really interesting, ed that years ago, you know, nobody
in my line of work covering tech sector like I
have for decades, would be interested in any utility company.
It's the antithesis of tech. They are boring, regulated, slow
growth businesses. However, now they've come to the four and
of course these are not just your regular utilities, you know,
(07:40):
they're your new era utilities. But yes, if you are
a good analyst, you have to cover the entire supply chain,
the entire ecosystem. And because demand is so robust, we're
focusing on supply absolutely critical. And it's not just the power.
There are physical constraints here, like simply pouring the cement
(08:04):
to build the next data center, which can't be a bottleneck,
even though it sounds, you know, so old school in
a new school business. But yes, these are some factors
that are very, very interesting that people didn't even conceive
of a couple of years ago.
Speaker 3 (08:20):
Pol is there an adequate federal level framework regulation to
support the energy requirements of the AI industry in this country?
Speaker 6 (08:32):
You know, there is not. And here is my problem.
We are still suffering from a lack of solid regulation
for the Internet because even today in the US the
Internet is operating under nineteen ninety six legislation when Bill
Clinton was president, and so I'm hoping that we're not
too restrictive.
Speaker 1 (08:52):
Right.
Speaker 6 (08:53):
We need to embrace our entrepreneurial companies and give them
room to roll, but we need to have some guards
else on everything AI because what happened last time is
we end up abdicating the legislation to the EU because
we didn't have the will to do it ourselves. So
we missed that opportunity in the Internet. Here is the
(09:15):
next wave. We need to embrace it and at least
come up with some guardrails that are going to guide
all this because there are some important decisions on the
federal level to be made.
Speaker 3 (09:27):
In your research pro it's very interesting to see you
approach data center from the perspective of yes, you know,
energy supply, but also real estate. The reats right, and
what you want to ask you is away from the GPUs,
where are the frailties in that industry? Is it literally
the folks building the tin can around the outside of
(09:48):
the data center, the labor, the concrete.
Speaker 6 (09:52):
Yeah, we've seen some hit in short term revenues because
a couple of the number or a few of the
players have subcontractors. Now this is not them, this is
their subcontractors.
Speaker 7 (10:04):
That are delayed.
Speaker 6 (10:06):
What we call building a powered shell. So it's more
than a quandset hut that you might find the army in.
These powered shells are a little bit more sophisticated. But
one company I cover had a one hundred and fifty
million dollars revenue deferral from twenty five to twenty six
because at one of their forty one data centers someone
(10:28):
couldn't pour concrete because it was raining. And so yes,
all these things come into play, and it's interesting that
they may not necessarily be technical bottlenecks, but old school
physical including construction bottlenecks. In addition to the power.
Speaker 2 (10:45):
I just go back from Vegas.
Speaker 3 (10:46):
With all the attention on artificial intelligence in the digital world,
we have an industry that's getting hit by a rainstorm.
Pool meeks, buckets, unbelievable. It's great to have you on
Bloomberg Tech. A lot more to come and coming out
an exclusive interview with the co founder and COO of
Minimax after the company just went public in Hong Kong,
(11:07):
and that's the debut trade.
Speaker 2 (11:08):
And this is Bloomberg Tech.
Speaker 3 (11:23):
Minimax, one of China's largest generative AI startups, backed by
Ali Barber and Abadavi Sovereign Well Fund, is now public.
Shares surge in Hong Kong after an IPO that raised
six hundred and nineteen million dollars, closing up one hundred
and nine percent in its Friday debut trading. Bloomberg Stephen
Engel spoke exclusively with co founder and COO Yee Yun
(11:46):
about growth and expansion plans as Minimax faces hot AI
competition both locally and globally.
Speaker 8 (11:54):
We really focus out that capital efficiency caused the efficiency,
so we had always spent a round five hundred media
USC in the in total, probably only one or two
percent of the biggen suspending, So we did all the organization,
mad creativity innovations on.
Speaker 9 (12:11):
The h How do you compete though, if you're going
to go global, how do you compete with an open
AI or others that are throwing lots of capital at
their business?
Speaker 2 (12:22):
Is it viable and what is the.
Speaker 9 (12:23):
Technology gap looking like in the next few years.
Speaker 8 (12:26):
Actually, I don't think it's a competition. It's more about
all the top talents across all the world. They bring
the technology break through to the society, to the end users.
So you will see each models have pros and accounts,
so we focus more resources on building the models, building
the best product experience to a more and more uses
(12:48):
from all the world.
Speaker 4 (12:49):
To use it.
Speaker 9 (12:50):
We're hearing as well, the Chinese government might approve in
Vidia's H two hundred for China in this quarter. Perhaps
is that something you need to look at importing more
advanced accelerators for your training.
Speaker 1 (13:03):
And the like.
Speaker 8 (13:04):
I think in every industry with a really high growth
when the new technology comes here, so you will see
every startups, all the companies. This please resources comestring probably
chief constring computing constring is only one of the challenges.
So in the past you will see our model performers
and our product performers, so our resources is stable. We
(13:26):
can get access to all of them, so we focus
more on our R and D and foundation model. So
we just use whatever chiefs who make sense for us
at that specific stage.
Speaker 9 (13:37):
Is your goal to stay indigenously with your chips locally
made chips or would you buy nvidio chips as well?
Speaker 8 (13:46):
It doesn't matter what kinds of chiefs it is. It's
more about which chiefs can give us best ROI, which
can help us to achieve our mission to make the
best technology too accessible to all of the users across
the world.
Speaker 9 (14:00):
So when does the emphasis turn from efficiency to profitability
and also getting that steady revenue growth that will then
justify a higher stock price valuation.
Speaker 8 (14:12):
So we put loss of R and D resources and
innovations on the efficiency part. You will see our API
we have the enterprise business and you will see the
gross profit margin of our API is more than sixty
five percent, which is probably already one of the highest globally.
So we focus more on make the best technology and
(14:32):
the best the user experience that people would love to
pay for the best performers models for their use cases.
Speaker 9 (14:39):
You've also come out of a price war essentially a
race to the bottom some have called, because of you're
trying to keep costs down and you want to survive
as well. There was a battle of survival and you
have been one of the survivors. But at the same time,
the startups are not the only ones. The big players
Ali Baba, by Dads, tens and others. How do you
(15:02):
compete with them at a low cost basis?
Speaker 8 (15:05):
Actually it's not. I don't think that's a press word.
It's more about the performers the competition, So you need
to make your model best. And the people I mean
and the user are interpress customers. They don't choose your
model because of its cheap or expensive. It's more about
its performers. So that's the key. As you said, I
(15:26):
think it's not about the competition between like all these
big chenz, but it's more about some of them. They
are like our cloud providers and some of their products
you see our models, So it's more about the collaborations.
All this company brings the foundation models to all the world.
Speaker 3 (15:44):
Many Max co founder and COO Yaun speaking exclusively with
Bloomberg Steven Engel. Public listings in Hong Kong are hot
right now. Chinese industrial robot maker in Events is now
also considering a second listing in Hong Kong, according to sources.
Let's get out to Bloomberg Executive Tech editor Peter Elstrom.
Speaker 2 (16:02):
To discuss this.
Speaker 3 (16:02):
But also like this growing trend of more of China's
sort of post chat gbtai firms going public. The team
that you lead out in Asia busy right now. In
Events's case, what are the details in our reporting that
we need to know about.
Speaker 10 (16:18):
Yeah, there are a lot of these IPOs that we're seeing,
and we're seeing a much more forward move into the
public markets for a bunch of these companies and events
has already gone public in the mainland and Shenjen now
it's looking at an IPO in Hong Kong.
Speaker 11 (16:32):
Two.
Speaker 10 (16:32):
That's partly a reflection of how hot demand is from
investors for these kinds of companies. When you're talking about
Minimax in particular, they went public, as you mentioned, their
shares more than doubled in the debut. The founder of
the company is very fascinating. These are some people called
them the AI tigers, some people the AI dragons. But
these are startups that really have very very different strategies
(16:53):
for how they're approaching the market. Compared with some of
the US competitors, Like in open Ai, they tend to
be much lower cost models. They tend to be much
more aggressive about implementing the technology with their customers, with
corporate customers, and giving them very low cost, very low,
very efficient models that they can use and they can
actually deploy more quickly than some of the US counterparts.
Speaker 3 (17:13):
PETE in the world of technology or in financial market's
like a term like an AI tiger or AI dragon.
Speaker 2 (17:18):
You know, it's kind of commonplace. We bandy it around.
Speaker 3 (17:21):
But for those watching Bloomberg Tech that are saying, what
are you talking about? How do we define the AI tiger?
What are we talking about here?
Speaker 10 (17:28):
Well, we're talking about a whole series of companies coming
out of China. In Stevens interview with the Minimax COO,
they talked about the competition there. We've of course heard
a lot about Deep Seek and how good their model is,
how technically good it is, but also how low cost
it is. Behind Deep Seek, you have a whole bunch
of other companies like Minimax, like Jipou, which just went
(17:48):
public on Thursday. So yeah, the IPO of Geepoo on Thursday,
mini Max on Friday investors showed a lot of demand
for those shares. And what these companies have been able
to show is that with a very low cost model,
they're out there in the market competing. It's not clear
that they're going to be able to compete directly with
Open AI or Anthropic, but they have very innovative models.
I mean, first of all, the US models are not
(18:09):
going to be let into the China market. But these
companies are also going out very aggressively and competing in
some other parts of the world. We've written about how
much traction Deep Seek is getting in Africa in particular,
because their companies are sensitive to costs. They're sensitive to
how much power, how much computer resources they need to
be able to deploy these models. So they are having
some successes. We're going to see a lot of competitive
(18:31):
clashes in the months ahead.
Speaker 2 (18:33):
Bloomberg's executive editive for Tech, Peter Alstrom. Great to catch
up with you, Thank you so much. Now coming up
on the.
Speaker 3 (18:38):
Program, Love Musks Grock image generation tool faces backlash after
reports that's generated thousands of undressed women and children.
Speaker 2 (18:48):
Go more on that data. Next, this is Bloomberg Tech.
Speaker 3 (19:00):
Elon Musk's AI startup Xai is burning cash quickly. The
company spent almost eight billion dollars in the first nine
months of the year. That's according to internal docs that
Bloomberg's viewed. Though revenue has nearly doubled quarter over quarter
to one hundred and seven million dollars, Xai's losses have
been mounting on costs to build data centers, recruit talent
(19:22):
developed software and to build AI that is self sufficient,
and according to Bloomberg's reporting, the plan is to use
that AI to eventually power Tesla's humanoid.
Speaker 2 (19:33):
Robots in the Optimus program.
Speaker 3 (19:35):
Right Sticking with XAI, the company has limited access to
Grock's image generation tool for most users, following widespread criticism
that the feature was producing thousands of explicit images of
women and children. Bloomberg reporter Cecilia Deannastasio broke, the story
has been tracking the developments, Cecilia, that we just summarized
(19:58):
the issue, right think, let's start with the methodology, how
we went about looking at the data, how we got
the data, and we'll go from that.
Speaker 1 (20:07):
Thank you for having me. Bloomberg worked as a researcher
who scraped thousands of images produced by groc and published
to the platform X between the period January fifth and
January sixth. The researcher analyzes images to determine what percent
of them were sexualized and neudifying, and found that every
hour during that twenty four hour period, X was publishing
about six thousand, seven hundred images identified as such, and
(20:31):
just for a comparison, websites that are dedafied dedicated to
publishing deep faked images AI generated images of women who
are sexualized neudified. Those top five websites out there published
together eighty images per hour. So GROC is one of
the biggest deep fake producers on the Internet today.
Speaker 2 (20:51):
Where are these images showing up?
Speaker 3 (20:53):
You know, to the uninitiated people may not know the
sort of interconnects between XAI the AI company, and x
the social media platform, for example, but they are now
kind of one entity as they combine last year.
Speaker 1 (21:08):
Well, that connection is exactly why x has become one
of the biggest deep fake websites on the internet. Anybody
can well not anybody now, now you have to pay
to do this, But over the last couple of days,
anybody could just at rock on the X platform and say,
put this woman in a bikini under an image that
a woman had post on the internet. And a lot
of women women primarily are the victims of this, took
(21:30):
to complaining to GROC directly and arguing with GROC in
their comments.
Speaker 7 (21:34):
GROC would apologize for posting.
Speaker 1 (21:36):
These images, but then continue posting them and not take
down Many of the images that the women felt were violating.
Speaker 3 (21:42):
Succeed That did X or XAI respond to our reporting,
engage with us on it.
Speaker 1 (21:49):
X has not responded to our numerous requests for comment
over the last couple of days. Elon Musk himself, in
a reply to a post on X said anybody using
groc to make illegal con tent will suffer the same
consequences as if they upload a legal content, and Musk
there was referring to allegations we believe of child sexual
abuse material that's been posted to X using the croc app.
Speaker 3 (22:12):
Okay, Bloomberg's the CID Danna Slasio important reporting.
Speaker 2 (22:15):
Read the story on the Bloomberg terminal on bloombuw dot com.
Thank you.
Speaker 3 (22:19):
Now, coming up from the program, we're going to speak
with Snowflake CEO Shrida Ramaswami. Is the company enters into
an agreement to buy AI powered platform observe. We'll get
his observations on that piece of M and A that's
coming up next. You're halfway through the program, and this
is Bloomberg Tech. Welcome back to Bloomberg Tech. I've been
(22:51):
using the power of my Bloomberg terminal. It's been a
long week with cs and Las Vegas. The power of
my brain is dwindling. But it tells me that Apple
is down for an eighth straight session, which matches the
run of declines that Apple saw in May of twenty
twenty five.
Speaker 2 (23:06):
Now using more of the power of the Bloomberg terminal.
Speaker 3 (23:11):
If Apple was full for a ninth day, we think
that would be the longest run of decline since the
early nineties. And obviously we are only nine days into
twenty twenty six. But so far year to date, this
is a stock that's down five and a half percent.
You saw the letter from Tim Cook to shareholders talking
up the company's progress of late and last year, but
(23:32):
right now that stock heading down and will continue to
track it. We had some M and A in the
last twenty four hours, but it's actually in the AI
and software space. Snowflake has agreed to buy Observe, an
observability platform and AI powered observability platform. Observability something that's
come up a lot recently, particularly in the context of AGENTICAI.
(23:53):
When I've been around the table, particularly on the engineering side.
Why this piece of M and A? Why now that's
sorts of Snowflake CEO Treda Ramaswami. Those are the reasonable questions,
right SHREDA I do want to get to defining observability
and why it's important.
Speaker 2 (24:10):
But it's an interesting deal. Why do you do it?
Speaker 12 (24:14):
Hey?
Speaker 7 (24:14):
Great to see you.
Speaker 12 (24:15):
Snowflake's acquisition of Observe is a game changer for our customers.
As you pointed out, observability is basically looking at applications, websites,
AIA agents to make sure that they are functioning properly.
Speaker 7 (24:28):
It's a diverse and messy problem. It's a big data problem.
Speaker 12 (24:32):
And because observer is built right on top of Snowflake,
they are able to use our very efficient storage as
well as computer platform to help customers find problems ten
times faster, often at three to four x less cost.
Take a company like Top Golf, it's a customer of
(24:52):
a Observe. I go to Top Golf all the time
with my team, not much of a golfer, so I'm
playing an angry Bird's game or something like that. Top
Golf used to struggle when these games went down because
they collected everything in a central place but could not
identify that a particular booth had problems. They're able to
do that with Observe in a matter of a few seconds,
(25:13):
send out a tech team to go fix that problem
and have happy customers.
Speaker 7 (25:17):
That's the power of this acquisition.
Speaker 12 (25:20):
Increasingly, capabilities like observability are going to be a core
part of a platform like Snowflake. And we have great
customers folks like Barclays, Capital One, Commonwealth Bank of America,
and we're super excited to bring this to over ten
thousand plus customers on Snowflake SHREDA.
Speaker 3 (25:40):
Let's get it out the way if we can. The
report saw that it's about a billion dollar deal. What
was the structure of the deal and the financials on it?
Speaker 2 (25:47):
Please?
Speaker 12 (25:49):
We can comment on the structure of the deal it is,
you know, some of it will come out in the
some of it will come out in the filing.
Speaker 3 (26:00):
Signal that there might be some more pieces of M
and A, particularly on that layer that you sit on
right you know, as you know very well you were
there on Monday at the video event Jensen talks about
the five layer cake and one of the layers you occupy.
But as observability evidence is, there might be pieces of
competency missing. How are you going to use M and
(26:21):
A to plug those gaps.
Speaker 12 (26:24):
We've been pretty open that we want to be an
end to end data platform for our customers from the moment.
Data is barn when you interact with an application, for
example two, bringing it in for analysis, analyzing it, and
then acting on it increasingly with AI agents. We've been
systematically going through this process of both acquiring customers and
(26:47):
building up.
Speaker 7 (26:48):
Functionality from within.
Speaker 12 (26:51):
Things like observability or data clean rooms are adjacent functionality
that sit on top of a data layer. You will
continue to be super act about both spinning up new
projects internally and acquiring companies. I think the environment is
right for that, and honestly, our customers want that because
they're spending entirely too much time just stitching things together,
(27:13):
and we make it seamless and easy to use for that.
Speaker 2 (27:16):
How competitive is that m and a environment right now?
Speaker 3 (27:19):
Because when I look at Observe and what it's offered, you,
you know, the analysts looked at that deal and said
completely logical that Snowflake would do it. But one would
imagine that there would be others in the market for
a name like Observe as well.
Speaker 2 (27:34):
Well.
Speaker 12 (27:34):
There are many things that we're going for this particular deal.
As I said earlier, Observer is built on top of Snowflake,
which means that we didn't have to deal with a
long integration cycle. The products are super tight. We've been
collaborating closely with the team as partners for a very
long time. I've actually gone and visited the Observed team
(27:56):
multiple times in their location in San Mateo. We felt
like this was a natural extension of who we were
as a platform, and we think that Observed, by using
both their technical capabilities and now also being part of Snowflake,
can offer an incredibly cost competitive solution. Cost has been
(28:17):
a big factor in the world of observability, especially with
things like AI agents, which are complicated pieces of software
that generate enormous amounts of essentially telemetry information.
Speaker 7 (28:28):
We think this is a good combination that's.
Speaker 3 (28:31):
Worth some academic debate, you know, should I'm not a
computer scientist or an engineer, right, so so take that
into account. But the thing that we argue about with
a truly autonomous AI agent is that it's exactly that
it is supposed to act. With autonomy and observability raises
the question of if a human is required at some
(28:53):
point in the process to check.
Speaker 2 (28:56):
In, what's your point?
Speaker 12 (28:58):
You know, well, it becomes a matter of how many
people you need in order to accomplish a problem. So
I live and breathe agent Kai. I mean, I really
mean that I use these products every single day. And
the leverage that you get is the game changer. Used
to be that a support ticket would come and a
(29:18):
person had to go read the text of what that
case was, copy and paste that text into multiple tools,
figure out what is going on, and then perhaps send
a Slack message over to somebody in order to answer
a problem.
Speaker 7 (29:30):
A lot of this, as you know, is low value work.
Speaker 12 (29:33):
Copying information from one screen or one app to another
is just tedious, it's no fun. I think the power
here with Agentic systems is going to be all that
boring stuff is going to be automated, so that when
a problem comes in, you go reach out to the
ten tools that you need to collect information from, you
analyze it, and then you show that somebody to that
(29:54):
person who decides what action to take.
Speaker 7 (29:57):
But furthermore, if they have to go write.
Speaker 12 (29:59):
Some custom gode to solve a new problem, they'll do
it two three times and turn that into a skill
that can be used by everybody else. I think it
leverages people enormously. I can tell you again from personal
experience that I can get stuff done in a matter
of a couple of hours on top of Snowflake building
things that would honestly have taken me two to three
weeks just last year to get done.
Speaker 3 (30:21):
That's the game changer that's here treat us. Snowflake rose
forty two percent last year. What are the goals that
you're holding you and the team to for twenty twenty
six and the things that you want to achieve this
year in AI?
Speaker 12 (30:37):
As you know ed, it's important to focus on the
things that you can control. What we're super excited for
twenty twenty six is making agent ki.
Speaker 7 (30:47):
Come alive for all our customers.
Speaker 12 (30:50):
Snowflake Intelligence is our agentic data product and it's been
a game changer again for me to do things like
do research on customers before I meet with them. This
is the fastest product in terms of customer adoption and
revenue in Snowflake's history. We want to make sure that
we drive adoption of these products, and in turn, what
(31:13):
this does is it enhances and makes the power of
data more and more visible to future customers. I expect
this AI to be a strong pull that makes data
modernization much much more relevant part every customer and future
customer of Snowflake.
Speaker 3 (31:31):
It is really that in and yang that I'm super
excited about. We started the week together in Las Vegas
at the Nvidia keynote. We end the week together talking
about the roadback from part four the Snowflake. Snowfake CEO
Shreeta Ramaswami. Great to have you back on Bloomberg Tech.
Speaker 2 (31:45):
Thank you.
Speaker 3 (31:45):
Now coming up, we're going to take a look at
the state of media mergers as one of brows sticks
with its buyout by Netflix and it's trying to shake
off that paramount takeover.
Speaker 2 (31:55):
We have the details. Next, this is Bloomberg Tech.
Speaker 3 (32:05):
Lairs of Netflix have tumbled nearly twenty eight percent since October,
but the streaming giant stock still appears to be too
expensive to many investors. Here of more is Bloomberg Stock Reporter,
All Things Terminal, authoring Squawk Police Morantz.
Speaker 2 (32:20):
This is a really important write up.
Speaker 3 (32:22):
Right there is so much hype and a lot of
headlines around what's happening with Warner Brothers Discovery.
Speaker 2 (32:27):
And you do what you needed it.
Speaker 3 (32:29):
You go back to basics, look at the fundamentals, look
at the stock to must read on the Bloomberg Tamila
dot com. But just I guess give us the top
line of the reporting.
Speaker 13 (32:37):
The top line is that this stock has really plunged
since investors started questioning whether this deal was a good
idea or not.
Speaker 7 (32:45):
You have questions about cost, You have integration risk as.
Speaker 13 (32:49):
Netflix doesn't have much experienced swallowing large deals, and you
also have a big regulatory fight that's looming. So there's
not a lot of extreme enthusiasm about the stock right now.
Speaker 7 (33:04):
In fact, it's down.
Speaker 13 (33:05):
You can see it's down about two percent today on
an update for the S.
Speaker 7 (33:08):
And P five hundred.
Speaker 3 (33:10):
The people you speak to it in the piece, you know,
one of the anecdotes is like Netflix is not screaming
by right now. Right But you also, I guess, look
at multiples, current multiples and historic multiples and compare them.
Speaker 2 (33:22):
What would that tell us?
Speaker 7 (33:24):
So there are various different kinds of multiples.
Speaker 13 (33:27):
But if you look at a basic price to earnings ratio,
the stock is not expensive historically, but Nora is it
very cheap.
Speaker 7 (33:36):
It's training a.
Speaker 13 (33:37):
Bit below its historic norm, but not enough to really
grab people.
Speaker 3 (33:44):
Bloomberg's police morans is awesome and it's been great to
have you back on bloombog take this Friday.
Speaker 2 (33:49):
Thank you very much. I want to get deep. You're welcome.
Let's get deeper into that deal.
Speaker 3 (33:54):
Part the future of streaming the Warner Brothers Discovery Saga
and then the two bids Matthew Dolgan, morning Star Senior
around equity and this covering communication services.
Speaker 2 (34:03):
Felice did a good job right going over the stock.
Speaker 3 (34:06):
But there's a piece of the deal that I asked
the team to find someone to dig in with us on,
which is do we value the cable networks part of
Warner Brothers Discovery at zero?
Speaker 2 (34:19):
Which paramount?
Speaker 3 (34:20):
When it reaffirmed it's thirty dollars a share bid came
out with your take on that.
Speaker 14 (34:25):
No, we don't think it should be valued at zero. However, well,
first of all, there is a risk that it could be.
We don't think that that's right. But this is going
to be a very heavily debt laiden company and that
leads to more risk, and so it's possible that zero
it would be in the future. We don't think that's
the most likely thing, but there is question of whether
it's worth two dollars a share or three dollars a
(34:47):
share or more and that matters because that is what's
making up the difference between what Netflix offered for the
portion of Warner Brothers Discovery that it wants versus what
Paramount offered for the your company. And so there are
a few different moving parts as you compare the deals,
which are not apples to apples. But it doesn't have
to be zero. If it's one dollar, like Paramount has
(35:10):
said previously, and this week with versants trading, that adds
another potential new data point, but it can be definitely
less than what the thirty is combined.
Speaker 3 (35:21):
So I'm just going to recap for the Bloomberg Tech audience.
Here's where we stand. Netflix has offered twenty dollars twenty
seven dollars a share for the streaming and the studios
and would plan to spin out the legacy cable networks.
And as we've said for five days in a row
on Bloomberg Tech, Paramounts Guidance want the whole enchilada, all
of it, but at thirty dollars a share, saying that
(35:42):
they assume a zero dollar value for that cable network.
You're covering the space, and you're covering these names, and
you're covering the deal. It's actually a very reasonable question
of what happens next. Because Warner Brothers board sent a
letter reject the Paramount offer and explained why. The next
(36:03):
day Paramounts guidence reaffirm that offer. We just continue in
that cycle.
Speaker 2 (36:08):
Well, we continue in that cycle for a little bit.
Speaker 14 (36:10):
Yes, January twenty first is a critical date that we
should circle on our calendars. That's when the tender offer
for the Warner Brothers Discovery shares by Paramount is currently
set to expire. So we'll see what happens at that point.
It doesn't appear that right now Paramount is likely to
get a sufficient number of shares by that date, but
(36:31):
they can extend it, extend the date, and they can
also well at any time. But that's when we would
expect potentially they would look at increasing their offer to
beyond thirty dollars a share. And so, yes, we do
kind of wait and see the next development. I don't
really expect anything until close to the twenty first as
far as new information. But at this point we'll see
(36:52):
where Paramount is on the shares that are being tendered,
and then the ball is kind of it's kind of
in its court as far as whether it wants to
do something else in the interim before later this spring
or summer, when Warner Brothers Discovery shareholders are likely to vote,
and that Netflix deal that the Warner board has recommended.
Speaker 3 (37:13):
We spend a lot of time this week talking about
the Warner Brothers Discovery rationale for rejecting Paramoun's guide on
so we included debt. It included a discussion either negative
or positive about Larry Allison being the bank stop on
the deal, and it talks about the restrictive covenants on
Warner Brothers not being able to make major investments what
(37:33):
in this interim period. But the question actually I have
is who would get the most out of those assets HBO, Max,
the catalog and then the studios, Like which company would
be better at getting them out into the real world
to your mind?
Speaker 14 (37:48):
Well, we think Paramount is the company that I guess
needs them more and probably would benefit from them more.
As far as getting them out into the world, that well,
arguably would be more Netflix a side with the business
they already have in place in the streaming service and
subscribers they already have in place. But if you're looking
from a business and an operating point of view, we
(38:11):
think Netflix has far less to gain as it does
that than Paramount would, which really needs the scale and
has I think a better combined type of offering, whereas
Netflix incrementally is sure it adds quite a bit to
it as far as incrementally on how much more revenue
that bring in, whether they're cannibalizing some of the profits
(38:31):
that Warner takes in with some of its licensing. The
reasons why we think that from a business standpoint, Netflix
doesn't benefit quite as much as Paramount would. That's of
course a maybe different question than what the consuming public
and how they benefit from the content and the availability
and the pricing for that.
Speaker 2 (38:48):
It's out there.
Speaker 3 (38:50):
You heard Felice's reporting on the stock why very quickly
we just have thirty seconds? Has that sentiment with Netflix
soured since the deal first kind of got announced.
Speaker 14 (39:02):
As far as the deal goes, I think there's been
some fear that Netflix would even pay more. There's also
some fear they've overpaid with what they've agreed to already,
so that may not be worth it. I also think
it's maybe just brought to light some things that we
had been thinking about for some time, even apart from
what's going on with Warner, which is the growth is
(39:22):
set to slow at Netflix, and therefore the multiples that
it had historically aren't necessarily justified today. And so if
it is at lower motiles now, which it certainly is
where compared where it's been historically, that's probably justified. Being
the growth outlook now versus in the past.
Speaker 2 (39:37):
We got to leave it there.
Speaker 3 (39:38):
But that brings us a nicey full circle to what
police was talking about at the start of the block.
Speaker 2 (39:41):
Matthew Dog in the morning, so thank you very much.
Speaker 3 (39:43):
Now coming up, Intel CEO was at the White House
to deliver a progress report on its activities. The US
government is its big shareholder that it's being accounting to.
Bit more on that next, as the Bloomberg Tech for
Talking Tech first up, Vodafone Idea is considering raising debt
(40:08):
financing to accelerate growth.
Speaker 2 (40:10):
That's according to sources.
Speaker 3 (40:11):
This comes after Delhi decided to cap annual payouts for
past spectrum fees, forerring a lifeline to the country's third
place carrier that's out in India. Plus compensation for Apple
CEO Tim Cook held steady at a cool seventy four
million dollars last year. Just three million of that comes
from salary, though the rest is in the form of
(40:31):
stock awards. You may remember a few years ago Cook
was criticized for pay packages close to one hundred million
dollars apiece, prompting him to request a compensation reduction, and
TSMC provided an upbeat sales forecast. The company reported a
roughly twenty percent rise in the December quarter revenues based
on calculations off monthly figures. The company reports full quarterly
(40:53):
earnings next week. All this coming after chip makers projected
optimism for AI demand at cs this week. Now, sticking
with Chips, shares of Intel up today in a big way.
Of the company's CEO delivered a progress report on its
company's U line of processors. At the White House, Libutan
met with President Trump and Commerce Secretary Howard Lutnik. After
(41:14):
the meeting, Trump praised Intel and said the government was
proud to be a shareholder.
Speaker 2 (41:20):
For more.
Speaker 3 (41:20):
Let's get out to Bloomberg's Ian King, who of course
leads our coverage of Chips. Actually, where I wanted to
start in is the President in his post talked about
the result of the government's investment in Intel, yielding I
think said tens of billions of dollars for the American people.
It's important probably to do the math on what the
actual return would be at this stage.
Speaker 2 (41:41):
Please.
Speaker 11 (41:43):
Yeah, no, I mean, as taxpayers, we own currently about
eleven billion dollars worth of Intel stock, and that's a
nice return, roughly twice what we owned when we made
the investment as a nation last year, and not in
the tens of billions. For that to happen, obviously Intel's
(42:03):
share price would have to go up a lot more,
and or some ex extra kind of arrangements that exists
would have to be bigger.
Speaker 3 (42:14):
All the same that there has been some stock performance
here since lit Bhutan kind of had this improvement in
relationship with the president. What do we know about yesterday's
meeting and kind of where Intel's focus right now in
what it's trying to tell the US government.
Speaker 11 (42:30):
Yeah, I mean, you know, the fact that he's in
the White House is important because that is basically drawing
attention to the fact that this investment that we saw
last year from the US government from in Nvidia, from
SoftBank has really stabilized Intel's kind of balance sheet, and
so it's in a much stronger position than it was.
(42:50):
But where we are and where we really need to
be is to have much better operations and much better
performance from the company, and that is going to take
new products. You and I were at CES this week
and we saw Intel come out and say, hey, here
are our new chips. These are the ones we promised.
These are the ones that they are going to deliver. Obviously,
three or four days into that launch, we don't know
how well they're going to do yet, but at least
(43:12):
in terms of the specs, way better than the position
that Intel has been in.
Speaker 3 (43:17):
And again a large portion of the government's ownership of
Intel is contingent on performance of those goals. Bloomberg Z
and King, Happy Friday to you and thank you very much.
That does it for this edition of Bloomberg Tech in
what's been a monster week. Frankly, just back from Las
Vegas and see yes and the headlines keep coming, particularly
in the world of AI. Great place to recap the show,
(43:37):
the week, the interviews and the reporting is on the podcast.
You know where to find it online, Apple, Spotify, iHeart
and all the Bloomberg platforms.
Speaker 2 (43:44):
Happy Friday. This is Bloomberg
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