"I'm EXPOSING this NO MATTER what..." - Chamath Palihapitiya On Nvidia Stock
Summary
TLDRThe video delves into Nvidia's staggering $247 billion single-day market cap gain, sparking discussions on the sustainability of its growth trajectory and potential competitors vying for a slice of the lucrative AI market. Experts analyze Nvidia's unique positioning, the complexity of its chips, and the driving forces behind major tech companies' aggressive investments. However, concerns arise over the absence of revenue-generating AI applications to justify the current spending spree, raising questions about the terminal value of Nvidia's dominance. As the AI revolution unfolds, the industry eagerly awaits the emergence of groundbreaking applications that could reshape the landscape.
Takeaways
- 😮 Nvidia experienced a record-breaking $247 billion single-day gain in market cap, following its exceptional quarterly results and projections.
- 🤖 The surge in demand for Nvidia's AI chips is being driven mainly by big tech companies like Amazon, Google, and Microsoft, as they race to build infrastructure for upcoming AI applications.
- 🏭 However, most of the current AI applications are still proofs of concept and demos, rather than fully-fledged production systems.
- ❓ There are questions about the sustainability of Nvidia's growth and whether new competitors will eventually emerge to compete away its profits, as typically happens in capitalism.
- 💰 The accounting treatment of these AI chip purchases as capital expenditures, rather than operating expenses, has incentivized big tech's massive spending on Nvidia's products.
- 🌐 The internet's history suggests that if the infrastructure is built, innovative applications will eventually follow to utilize it, driving long-term demand.
- 👨💼 Enterprise adoption of AI, in addition to consumer applications, is expected to be a significant driver of demand for Nvidia's products.
- 💥 While Nvidia's valuation has skyrocketed, some analysts question whether it can sustain a market cap comparable to the size of the economy its products may enable.
- 🚀 There is a belief that AI is still in its early stages, with a decade-long wave of new applications and innovations yet to come, further fueling demand for Nvidia's offerings.
- ⚠️ Concerns remain about the potential emergence of cheaper, alternative solutions that could disrupt Nvidia's dominance in the long run.
Q & A
What triggered Nvidia's significant market cap gain mentioned in the script?
-Nvidia's significant market cap gain was triggered by their overwhelming success and earnings in the AI and computing sector, leading to a $247 billion increase in market cap.
Why are most AI applications today considered 'toy apps' according to the script?
-Most AI applications are considered 'toy apps' because they are primarily proofs of concept and demos run in a sandbox environment, not production-level code or applications integrated into critical systems.
How did Meta's focus shift and layoff strategy affect its market cap earlier in the year?
-Meta's focus shift and decision to lay off 20,000 people, after its exploration into Reality Labs, positively affected its market cap, adding $196 billion.
What does the script suggest about the sustainability of Nvidia's profits from competitors?
-The script suggests that Nvidia's substantial profits may eventually be competed away, as in capitalism, over-earning attracts competitors who aim to capture a portion of those earnings, particularly in the absence of a monopoly.
What was Freeberg's perspective on the possibility of Nvidia becoming a 10 trillion dollar company?
-Freeberg discussed the accelerated compute buildout in data centers and the potential for Nvidia, considering whether the initial infrastructure investment will generate equivalent or greater value in the application layer.
Why is Nvidia's current success seen as a potentially temporary phenomenon?
-Nvidia's current success is seen as potentially temporary due to the risk of new competitors entering the market with lower cost solutions or innovations that could erode Nvidia's market share and profits.
What does the script mention about the importance of the application layer for future profits?
-The script highlights that the long-term value and profitability in the tech industry may eventually shift towards the application layer, as infrastructure buildouts reach completion and new applications generate revenue.
How did the script compare Nvidia's situation to historical examples like Cisco and Oracle?
-The script compared Nvidia's situation to Cisco and Oracle, noting how early dominance in hardware and infrastructure did not guarantee long-term market control as cheaper, more efficient solutions emerged.
What accounting advantage do big tech companies have when investing in infrastructure like Nvidia's chips?
-Big tech companies can account for large purchases of Nvidia's chips as capital expenditures, allowing them to spread the cost over several years on the balance sheet, rather than taking an immediate hit to the income statement.
How does the script suggest Nvidia's future market position will be determined?
-Nvidia's future market position is suggested to be determined by the total addressable market (TAM) for GPUs, Nvidia's sustained market share, and the balance between infrastructure buildout and the creation of new, profitable applications.
Outlines
🤯 Nvidia's Astronomical Market Cap Gain
The video discusses Nvidia's unprecedented single-day gain of $247 billion in market capitalization, attributed to the growing demand for their AI chips from major tech companies. It highlights the current state of AI applications as primarily proofs of concept and demos, rather than full-scale production systems. The discussion also touches on the uncertainty surrounding Nvidia's ability to sustain such growth and maintain their competitive edge in the face of potential competitors aiming to capture a share of the lucrative AI market.
🧐 The Real Value Proposition Behind Nvidia's Growth
The discussion delves into the driving factors behind Nvidia's revenue surge, primarily the substantial spending by major cloud service providers and tech giants on Nvidia's AI hardware. However, the real question raised is whether the current demand and revenue will translate into tangible long-term value creation. The panelists debate the potential for new competitors to emerge and compete away Nvidia's profits, drawing parallels to historical examples like Cisco and the early days of the internet build-out. The crux of the matter is whether the current spending is a precursor to sustained revenue generation from viable AI applications or merely a temporary buildup phase.
📈 The Accounting Drivers Behind Big Tech's AI Spending Spree
This part of the discussion delves into the accounting mechanisms and motivations behind the massive AI infrastructure spending by major tech companies. It highlights how these companies can capitalize their AI hardware purchases, allowing them to spread the costs over several years while utilizing their substantial cash reserves. The panelists discuss the implications of this accounting treatment, suggesting that it incentivizes cloud service providers to invest heavily in building out the next generation of AI infrastructure, even if the immediate revenue generation from AI applications is uncertain. The discussion underscores the complex interplay between accounting practices, cash reserves, antitrust concerns, and the drive for technological dominance in the AI domain.
⚖️ Assessing Nvidia's Long-Term Market Value and Competitive Landscape
The conversation shifts towards evaluating Nvidia's long-term market value and the competitive dynamics that may shape the AI hardware market. The panelists discuss the potential for Nvidia's market share to decline as new competitors emerge, while acknowledging the challenges associated with developing and manufacturing advanced AI chips. The discussion also explores the distinction between one-time infrastructure buildout and sustainable, recurring revenue streams, raising questions about the terminal value of Nvidia's AI business. Historical analogies, such as the dotcom bubble and the subsequent emergence of new applications and services, are drawn to illustrate the potential for AI applications to drive sustained demand for AI hardware over time.
🔮 The Future of AI Applications and Infrastructure Demand
The final part of the discussion focuses on the future potential of AI applications and the resulting demand for AI infrastructure. The panelists acknowledge that while the current demand is driven by major tech companies building out cloud data centers, the true value creation will come from the development of innovative AI applications across both consumer and enterprise domains. Drawing parallels with the history of the internet and the eventual adoption of broadband and streaming services, the discussion suggests that the AI infrastructure buildout today may pave the way for a wave of new AI-enabled applications and services in the coming decade. The conversation highlights the potential for sustained demand for AI hardware, provided that the applications and use cases continue to evolve and drive technological advancement.
Mindmap
Keywords
💡Market Cap
💡AI Applications
💡Production Code
💡Competition
💡Monopoly
💡Cloud Infrastructure
💡Data Centers
💡Capital Expenditure
💡Terminal Value
💡Revenue Recognition
Highlights
The overwhelming majority of the apps that we're seeing in AI today are toy apps that are run as proofs of concept and demos and run in a sandbox it is not production code.
Nvidia added $247 billion in market cap in a single day, one of the largest single day gains in market cap.
The real question is who will step up to try to compete away Nvidia's profits, as competitors will eventually try to compete away over-earnings in the absence of a monopoly.
The question is whether the initial cost of the infrastructure will exceed the ultimate value that's going to be realized on the application layer.
The infrastructure buildout is the first phase, and the real question is whether the applications and tools built on top of that infrastructure will justify the cost.
GPUs are much more complex and harder to commoditize than the networking equipment Cisco was selling, which made it easier for competitors to eventually erode Cisco's dominance.
Big tech companies are buying Nvidia's products because they have cash sitting idle, and they can capitalize the expenditure on their balance sheets instead of taking a hit on their income statements.
The accounting environment is motivating big cloud providers to build out the next generation of infrastructure, as they can't grow through M&A due to antitrust concerns.
There's a question of how much of Nvidia's revenue is sustainable ongoing revenue versus a one-time buildout.
Nvidia's market share is expected to decline from the current 91%, but analysts still expect them to have a 60% market share in 5 years.
The key question is what the total addressable market (TAM) for GPUs will be, and what Nvidia's market share within that TAM will be.
There is a framework for evaluating Nvidia's potential market cap by comparing the expected economy it will enable to the market caps of companies like Intel and Microsoft that enabled previous technological economies.
The history of the internet shows that if the infrastructure is built, applications will eventually be developed to use that capacity.
AI applications are expected to be developed for both consumer and enterprise use cases, utilizing the cloud data centers that are buying Nvidia's GPUs.
We are likely at the beginning of a decade-long wave of new AI applications and creativity being enabled by the current infrastructure buildout.
Transcripts
this is the largest single day gain in
market cap most of the apps the
overwhelming majority of the apps that
we're seeing in AI today are toy apps
that are run as proofs of concept and
demos and run in a sandbox it is not
production code this is not we've
rebuilt the
entire autopilot system for the Boeing
and it's now run with agents and B and
all of this training that's not what's
happening so
$247 billion added in market cap
previously meta did something similar
earlier this year remember everybody was
down on that stock because they were
doing all the crazy stuff with reality
labs and then they got focused and laid
off 20,000 people they added $196
billion shth your general thoughts here
on something I don't think anybody saw
coming except for you and your
investment in Gro maybe and a couple of
others I think what I would tell you is
that the bigger principle and we've
talked about this a lot Jason is that in
capitalism when you over earn for enough
of a time what happens is competitors
decide to try to compete away your
earnings in the absence of a monopoly
the amount of time that you have tends
to be small and it shrinks so in the
case of a monopoly for example take
Google you can over earn for decades and
it takes a very very long time for
somebody to try to displace you we're
just starting to see the beginnings of
that with things like perplexity and
other services that are chipping away at
the Google Monopoly but at some point in
time all of these excess profits are
competed away in the case of Nvidia what
you're now starting to see is them over
earn in a very massive way so the real
question is who will step up to try to
compete away away those
profits the old Bezos quote right your
margin is my opportunity and I think
we're starting to see and you've
mentioned grock who had a super viral
moment I think this week but you're
starting to see the emergence of a more
detailed understanding of what this
Market actually means and as a
result who will compete away the
inference Market who will compete away
the training market and the economics of
that are just becoming known to now more
and more people freeberg your thoughts
we were talking I think
was last week or the week before about
possibility of Nvidia being a 10
trillion dollar company the largest
company in the world what are your
thoughts on the spectacular results and
then sh's point Everybody is watching
this going maybe I can get a slice of
that pie and maybe I can create a more
competitive offering obviously we saw
Sam hman rumored to be raising 7
trillion which feels like a fake number
feels like that's maybe the market size
or something but your thoughts here I
don't think anything's changed on the
Nvidia front there's this accelerated
compute buildout underway in data
centers everyone's building
infrastructure and then everyone's
trying to build applications and tools
and services on top of that
infrastructure the infrastructure
buildout is kind of the first phase the
real question ultimately will be does
the initial cost of the infrastructure
exceed the ultimate value that's going
to be realized on the application layer
in the early days of the internet a lot
of people were buying Oracle servers
they were like 3,000 bucks a server
and they were running these Oracle
servers out of an Internet connected
Data Center and it you know took a
couple of years before folks realized
that
for large scale distributed compute
applications you're better off using
cheaper Hardware you know cheaper server
racks cheaper hard drives cheaper buses
and assuming a shorter lifespan on those
servers and you could cycle them in and
out and you didn't need the redundancy
you didn't need the certainty you didn't
need the the runtime guarantees and so
you could use a lower cost higher
failure rate but much much net lower
cost kind of approach to building out a
data center for internet serving and so
the Oracle servers didn't really take
the market and early on everyone thought
that they would so I think Chamas point
is right now Nvidia has been at this for
a very long time and the real question
is how much of an advantage do they have
particularly that there is this need to
use Fabs to build replacement technology
so over time will there be better
solutions that use Hardware that's not
as good but the software figures out and
they build new architecture for running
on that Hardware in a way that kind of
mimics what we saw in the early days of
the build out of the internet so um TBD
right the same is true in in switches
right so in networking a lot of the
high-end high quality networking
companies got beaten up when lower cost
Solutions came to Market later and so
they looked like they were going to be
the biggest business ever I mean you
could look at Cisco during the early
days of the internet buildout and
everyone thought Cisco was the picks and
shovels of the internet they were going
to make all the all the values going to
agud to Cisco so we're kind of in that
same phase right now with Nvidia the
real question is is this going to be a
much harder Hill to compete on than
we've ever seen given the development
cycle on chips and the requirement to
use these Fabs to build chips it may be
a harder Hill to kind of get up SE so
we'll see your thoughts you think um
we're getting to the point where maybe
we'll have bought too many of these uh
built out too much infrastructure and it
will take time for the application layer
as freeberg was alluding to to monetize
it well I think the question everyone's
asking right now is are are these
results sustainable can Nvidia keep
growing at these astounding rates you
know will the buildout continue and the
comparison everyone's making is to Cisco
and there's this chart that's been going
around overlaying the Nvidia stock price
on The Cisco stock price and you can see
here the orange line is NVIDIA and the
blue line is Cisco and it's almost like
a a perfect match now what happened is
that at a similar point in the original
buildout of the internet of the Doom era
you had the market crash at the end of
March of uh 2000 and Cisco never really
recovered from that Peak valuation um
but I think there's a lot of reasons to
believe Nvidia is different one is that
if you look at nvidia's multiples
they're nowhere near where Cisco were
back then so the market in 1999 and
early 2000 was way more bubbly than it
is now so nvidia's valuation is much
more grounded in real Revenue real
margins real
profit second you have the issue of
competitive mode Cisco was selling
servers and networking equipment
fundamentally that equipment was much
easier to copy and commoditize than gpus
these GPU chips are really complicated I
think Jensen made the point that their
Hopper 100 product he said you know
don't even think of it just like a chip
there's actually 355,000 components in
this product and it weighs 70 pounds
this is more like a Mainframe computer
or something that's dedicated to
processing yeah it's somewhere between a
rack server and the entire rack yeah
it's Giant and it's heavy and it's
complex it does say something here
chamath I think about
how well positioned big Tech is in terms
of seeing an opportunity and quick
mobilizing to capture that opportunity
these servers are being bought
by you know people like Amazon I'm sure
Apple obviously Facebook meta I don't
know if Google's buying them as well I
would assume so Tesla so everybody's
buying these things and they had tons of
cash sitting around it is pretty amazing
how Nimble the industry is and this
opportunity feels like everybody is
looking at it like mobile and Cloud I
have to get mobilized quickly to not get
disrupted you're bringing up an
excellent point and I I would like to
tie it together with friberg's point so
at some point all of this spend has to
make money right otherwise you're you're
going to look really foolish for having
spent 20 and 30 and 440 billion so Nick
if you just go back to the to the
revenue slide of Nvidia I can try to
give you a framing of this at least the
way that I think about it so if if you
look at this like what you're talking
about is look who is going to spend 22.1
billion well you said it Jason it's all
a big Tech why because they have that
money on the balance sheet sitting idle
but when you spend $22 billion their
investors are going to demand a rate of
return on that and so if you think about
what a reasonable rate of return is call
it 30 40 50% and then you factor in and
that's profit and then you factor in all
of the other things that need to support
that that $22 billion of spend needs to
generate probably $45 billion of Revenue
m and so Jason the question to your
point and to Freed br's point the
$664,000 question is who in this last
quarter is going to make 45 billion on
that 22 billion of spend and again what
I would tell you to be really honest
about this is that what you're seeing is
more about big companies musling people
around with their balance sheet and
being able to go to Nvidia and say I
will give you committed pre purchases
over the next three or four quarters
and less about here is a product that
I'm shipping that actually makes money
which I need enormous more compute
resources for it's not the latter most
of the apps the overwhelming majority of
the apps that we're seeing in AI today
are toy apps that are run as proofs of
concept and demos and run in a sandbox
it is not production code this is not
we've rebuilt the
entire autopilot system for the Boeing
and it's now run with agents and Bots
and all of this training that's not
what's happening so it is a really
important question today the demand is
clear it's the big guys with huge gobs
of money and by the way Nvidia is super
smart to take it because they can now
forecast demand for the next two or
three
quarters I think we still need to see
the next big thing and if you look in
the past what the past has showed you
it's the big guys don't really invent
the new things that make a ton of money
it's the new guys who because they don't
have a lot of money and they have to be
a little bit more industrious come up
with something really authentic and new
yeah constraint makes for great art yeah
we haven't seen that yet so I think the
revenue scale will continue for like the
next two or three years probably for
NVIDIA but the real question is what is
the terminal value and it's the same
thing that Sach showed in that Cisco
slide people ultimately realized that
the value was going to go
to other parts of the stack the
application layer and as more and more
money was acred at the application layer
of the internet less and less Revenue
multiple and credit was given to Cisco
and that's nothing against Cisco because
their revenue continued to compound a
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maybe and Elon commented on this and he
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only guy that doesn't seem to know
anything about this but anyways in the
next couple of years this product might
even sell for thousands of dollars we
don't get that many chances to buy rary
Collectibles like this right and they
did an incredible job but the valuation
got cut so freeberg if we're looking at
this chart the winner of Netflix the
winner of The Cisco chart might in fact
be somebody like Netflix they actually
got you know hundreds of millions of
consumers to give them Cash go Facebook
and then you have Google and Facebook as
well generating all that traffic and
then YouTube of course who do you see
the winner here as in terms of the
application layer who are the billion
customers here who are going to spend 20
bucks a month five bucks a month
whatever it is so here well I mean let
me just start with this important point
if you look at where that revenue is
coming from to chamat point it's coming
from big cloud service providers so
Google and others are building out
clouds that other application developers
can build their AI tools and
applications on top of so a lot of the
buildout is in these cloud data centers
that are owned and operated by these big
tech companies the 18 billion of data
center Revenue that Nvidia realized is
revenue to them but it's not an
operating expense to the companies that
are building out so this is an important
point on why this is happening at such
an accelerated Pace when a big company
buys these chips from Nvidia they don't
have to from an accounting basis Market
as an expense in their income statement
it actually gets booked as a capital
expenditure in the cash flow statement
it gets put on the balance sheet and
they depreciate it over time and so they
can spend $20 billion of cash because
Google and others have 100 billion of
cash sitting on the balance sheet and
they've been struggling to find ways to
grow their business through Acquisitions
one of the reasons is they there aren't
enough companies out there that they can
buy at a good multiple that can give
them a good increase in profit the other
one is that anti trust authorities are
blocking all of their Acquisitions and
so what do you do with all that cash
well you can build out the next gen of
cloud infrastructure and you don't have
to take the hit on your p&l by doing it
so it ends up in the balance sheet and
then you depreciate it over typically
four to seven years so that money gets
paid out on the on the income statement
at these big companies over a seven-year
period so there's a really great
accounting and m&a environment driver
here that's causing the big cloud data
center provid to step in and say this is
a great time for us to build out the
next generation of infrastructure that
could generate profits for us in the
future because we've got all this cash
sitting around we don't have to take a
p&l hit we don't have to acquire a cash
burning business and you know frankly
we're not going to be able to grow
through m&a because of antitrust right
now anyway so there's a lot of other
motivating factors that are causing this
near-term acceleration as they're trying
to find ways to grow yeah and all this I
know I know that was an accounting point
but I think it's a really important
valid one if you if 100 billion gets
spent this year divided by four 25
billion in Revenue would have to come
from that or something in that range
yeah and so sax any guesses you have to
just keep in mind I think freeberg what
you said is very true for gcp spend but
not necessarily for Google spend it's
true for AWS spend but not necessarily
for Amazon spend and it's true for Azure
spend not true for Microsoft spend and
it's largely not true for Tesla and
Facebook because they don't have clouds
so I think the question to your point
that and for obvious reason Nvidia
doesn't disclose it is what is the
percentage of that 21 billion that just
went to those Cloud providers that
they'll then Expos to to to everybody
else versus what was just absorbed
because at Facebook Mark had that video
about how many h100s that's all for him
right but it is still it is still
capitalized as my point so they don't
have to book that as an expense it sits
on the balance sheet yeah and they earn
it down over time you're helping to
explain why these big cloud service
providers are spending so much on the
data CER because they're very profitable
and there's nowhere else to put the
money right well so that would seem to
indicate that this is more in the
category of onetime buildout than
sustainable ongoing Revenue I think the
the big question is the one that jamath
asked which is what's the terminal value
of Nvidia I think like a simple
framework for thinking about that is
what is the total addressable Market or
Tam related to gpus and then what is
their market share going to be right now
their market share is something like 91%
that's clearly going to come down but
the remote appears to be substantial the
Wall Street analysts I've been listening
to think that in 5 years they're still
going to have 60s something percent
market share so they're going to have a
substantial percentage of this Market or
this Tam then the question is I think
with respect to Tam is what is onetime
buildout versus steady state now I think
that clearly there's a lot of buildout
happening now that's almost like a
backfill of capacity that people people
are realizing they need but even the
numbers you're seeing this quarter kind
of understate it because first of all
Nvidia was Supply constrained they could
not produce enough chips to satisfy all
the demand their revenue would would
have been even higher if they had more
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second you just look at their forecast
so the fiscal year that just ended they
did around 60 billion of Revenue they're
forecasting 110 billion for the fiscal
year that just started so they're
already projecting to almost double
based on the demand that they clearly
have visibility into already so it's
very hard to know exactly what the
terminal or steady state value of this
Market's going to be even once the cloud
service providers do this big buildout
presumably there's always going to be a
need to stay up to date with the latest
chips right here's a framework for you
sax tell me if this makes
sense intel was the basically the mother
of all of modern compute up until today
right I think the CPU was
the the most fundamental Workhorse that
enabled local PCS it
enabled networking it enabled the
internet and so when you look at the
market cap of it as an example that's
about10 odd billion dollars
today the economy that it created that
it supports is probably measured call it
in a trillion or two trillion dollars
maybe five trillion let's just be really
generous right and so you you can see
that there's this ratio of the enabler
of an economy and the size of the
economy and those things tend to be
relatively fixed and they recur
repeatedly over and over and over if you
look at Microsoft it's Market cap
relative to the economy that it enables
so the question for NVIDIA in my mind
would be not that it is it not going to
go up in the next 18 to 24 months it
probably is for exactly the reason you
said it is super set up to have a very
good meet and beat guidance for the
street which they'll eat up and all of
the algorithms that trade the press
releases will drive the price higher and
all of this stuff will just create a
trend
upward I think the bigger question is if
it's a four or five trillion dollar
market cap in the next two or three
years will it support a hundred trillion
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just broken on the internet yeah I mean
so the history of the internet is that
if you build it they will come meaning
that if you make the investment in the
capital assets necessary to power the
next generation of applications those
applications have always eventually
gotten written even though it was hard
to predict them at the time so in the
late 90s when we had the whole.com
bubble and then bust you had this
tremendous buildout not just of kind of
servers and all the networking equipment
but there was a huge fiber buildout y by
all the telecom companies and the
telecom companies had a Cisco like you
know uh Peak it was worse you know wcom
and them they went bankrupt a lot of
them yeah well the problem there was
that a lot of the that happened with
debt and so when you had the dot crash
and all the valuations came down to
earth that's why a lot of them went
under yeah Cisco wasn't in that position
but anyway my point is in the early
2000s when the dotom crash happened
everyone thought that these telecom
companies had over invested in fiber as
it turns out all that fiber eventually
got used the internet went from you know
dial up to broadband we started doing
seeing streaming social networking all
these applications started eating up
that band with so I think that the
history of these things is that the
applications eventually get written they
get developed if you build the
infrastructure to power them and I think
with AI the thing that's exciting to me
as someone who's really more of an
application investor is that we're just
at the beginning I think of a huge wave
of a lot of new creativity and
applications that's going to be written
and it's not just B Toc it's going to be
B2B as well you guys haven't really
mentioned that it's not just consumers
and consumer applications are going to
use these cloud data centers that are
buying up all these gpus it's it's enemy
Enterprises too I mean these Enterprises
are using Azure they're using Google
cloud and so forth so there's a lot I
think that's still to come I mean we're
just at the beginning of a wave that's
probably going to last at least a decade
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