January 28, 2026 • 20 mins
In part two of this week’s Dot Com Bubble series, Ed Zitron explains the flimsy mythology used to convince the world to run millions of miles of fiber optic cable - and how completely different that is to building hundreds of billions of data centers of GPUs.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
Zone Media. I'm d Zetron and this is better offline.
That's right, folks, We're back for the second part of
our series in the dot Com Bubble and why I
(00:23):
believe the AI Bubble could be much, much worse. While
the dot com bubble was a mixture of dodgy venture
capital deals and websites that could never turn a profit,
combined with a global mania around the interconnectivity of high
speed Internet companies, the AI bubble is one company selling
expensive aigpus, a bunch of companies building data sentence to
put them in, and a bunch of companies building shit
(00:44):
that runs on GPUs that only loses money and that
customers kind of fucking hate. I should also note that
a very important part of the story is venture capital's
lack of returns in the last few years, something I
covered in the Hitter financial Crisis last week, specifically in
parts two and three. In simple terms, AI startups now
make up more than half a venture investment, and I
(01:04):
believe that most of these stops will die because of
their horrible margins, no part to profitability, and products that
people really don't want to pay for its scale, and
when they die, they will leave venture capitalists stranded with
tons of dead equity at a time when they already
have trouble generating returns and thus raising money from their
limited partners. The result, I worry, will be gruesome. Venture
(01:25):
capitalists make their money through the fees they generate, which
are based on the value of their investments and the
returns they give their investors, which don't seem to be happening.
What do you think happens when they can't generate any
returns and their investments aren't worth anything. The answer is simple,
they won't have any way of raising more capital as
their limited partners won't fucking trust them. And to be clear,
(01:45):
these arswapes have cocked it up many years at a time.
Look at crypto, look at NFTs, look at ar VR, metaverse,
all of that, and all of this ridiculousness has happened
because of the ridiculous, ridiculous myths of AI, like just
the insatiable demand for AI compute and the made up
decline in the price of intelligence, which, by the way,
(02:07):
that last one I've talked about it, I swear to god,
I mentioned it in the Guardia, mentioned it everywhere. It
may be cheaper to pay for the tokens, but you
use more of them, so it's more expensive in the aggregate.
On top of that, it doesn't mean that the price
of intelligence for the model providers is going down. Jesus Christ,
I'm so tired of making this points. But in both cases,
(02:30):
these assumptions are convincing investors that it's time to invest
in data centers that only lose money because you assume
that the demand will be there, or in AI startups
to only lose money because you'll assume they magically stop
losing money somehow. And it turns out we do actually
have a historical comparison. The mania of the dot com
bubble was based on a misunderstanding of the scale of
(02:50):
the Internet at the time, rather than its actual potential.
Hundreds of billions of dollars were invested based on flimsy logic.
To quote researcher Justin Kohler. This continental rewiring was also
justified by another powerful myth that Internet traffic was doubling
every ninety days. This claim spread through analyst reports, burning
course and investor presentations like a particularly virulent meme. If true,
(03:15):
it meant the demand was growing exponentially, far out pacing
any conceivable supply, and that every new trench of fiber
would soon pay for itself many times over. And I
pause here to go, oh god, they're doing it again.
Back to the quote. But the mathematics were fiction. Network
researchers like Andrew Adlisco at AT and T, looking at
actual traffic data, found that US backbone traffic was doubling
(03:38):
roughly once a year, rapid growth, certainly, but nowhere near
the purported ninety day cycle. Meanwhile, advances in fiber technology
were making each strand exponentially more powerful. Dense wavelength division
multiplexing allowed dozens of signals to travel simultaneously down the
same line a different wavelengths of light, like multiple conversations
happening in different colours. While demand doubled annually, supply expanded
(04:02):
tenfold or more. Carriers buried the discrepancy under layers of
creative accounting that would have impressed medieval alchemists. First of all,
justin if you hear this, I fucking love that. That
was very fun. Second of all, to quote twin peaks,
it's happening again. Mania had taken hold based on very
flimsy logic. Economically speaking, this meant the telecoms companies, serve
(04:25):
a hardware companies, ISPs, construction firms, optical cable providers, wireless
technology companies, and basically anybody related to the business of
providing Internet access in any way saw a massive influx
of business to build capacity that didn't need to be
built yet. If you're in the business of selling services
to get people online, you were high on the hug,
you know, kind of like selling high bandwidth rem Similarly,
(04:49):
one could get a startup funded if you had a website,
or even take in public. One could raise debt to
build a nascent ISSP or a fiber network. The money
was flowing because people people weren't really really being thoughtful
about it. And as far as the dot com part
of the dot com bubble, the unsustainable websites, the problem
wasn't so much the industry but the businesses themselves, which
were hyped and dumped onto the public markets with little
(05:11):
regard for their long term health. The problem here is
relatively simple. These were bad companies that people ignored the
issues with because of and they quote the power of
the Internet and how it would somehow save them, which
which it didn't obviously had they been kept private. And
died in the dark. I don't think these companies would
have had the same reputation. I don't think we give
a fuck about pets dot com. I also don't think
(05:34):
they were really in accurate comparison to anything happening today.
While the valuations were ridiculous, the Globe's market cap was
at one point eight hundred and forty million dollars, the
scale of destruction caused by dot com startups was significantly smaller,
even in today's money. The economics were bad, but not
anywhere near as bad. For the first nine months of
(05:55):
nineteen ninety eight, the Globe made two point seven million
dollars in revenue and lost eleven point five million dollars,
largely due to trying to move into multiple different business
lines at once like voice over IP. And to be clear,
this company made money selling ads and also buying random companies.
Buying random companies was the thing that happened during the
dot com boom. Everybody fucking loved buying companies. You just
(06:16):
bought random. There was I think like Excite, bought at Home,
like there was the AT and T sort, the Aol
time Warner merger. So many stupid mergers, so little time. Nevertheless,
the economics of this shit show were quite complex. You
had companies raising money to do any website they could
think of, companies raising money to lay fiber, companies raising
(06:39):
money to found ISPs, all of which had multifaested layers
of physical and digital infrastructure that were quite ugh unbuilt.
I think is the term. It's tempting yet incorrect to
say the thing about AI. The similarity everybody points to
is that people doubted the Internet at the time, and
people really need to remember their fucking history. In two
thousand and only fifty two percent of Americans who were
(07:01):
using the Internet. By two thousand and three, the number
had only increased the sixty one percent per the World Bank.
In two thousand and five, only sixteen percent of the
world used the Internet, and in twenty twenty four the
number had increased to seventy one percent. Yet the real
difference is the access to high speed Internet. When the
Internet was connected via a fifth to six K modem,
access was at times charged by the minute, and even
(07:22):
if it was unlimited, it was always much much slower.
While we're used to connecting its speeds that make using
web based app near indistinguishable from using one on a computer.
Back in two thousand, two thousand and one or two
thousand and two, the average US Internet speed was at
best four hundred kilobits per second, or roughly fifty killer
bytes per second, compared to the average US Internet speed
today of other two hundred megabits per second or twenty
(07:45):
five megabytes per second. In simpler terms than the younger
members of the audience won't understand this, A website took
time to load in a way that feels almost impossible
to conceive if you didn't experience it at the time,
you had to make a commitment to God all website.
It was like you've browsed multiple tabs and fuck around
the different windows. You sat there and you waited a
(08:05):
little bit. Sometimes it came up quick and then another.
In fact, websites like Google were quite popular because they
were very clean, and the reason that them being clean
wasn't usability. It was the fact it loaded quickly, which
I guess would be usability either way. We've also had
dramatic improvements in web design and accessibility. The advent of
mobile browsing and the proliferation of widespread mobile and desktop
(08:28):
Internet access in the two thousands, we were at the
very early days of e commerce, and the weird irony
of the dot com bubble is that it was actually
pretty useful to lay millions of miles of fiber optic cable.
This is in no way, shape or form remotely comparable
to large language models GPUs or any nebulous VC spunk
(08:48):
around Generative AI. Global Internet access has never been higher
or cheaper, and for the most part, billions of people
(09:09):
can access the connection fast enough to use Generative AI.
There is very little stopping anyone from using an LM,
Chat GBT is free, chat GPT's cheaper ghost subscription has
now spread to the entire world. When I originally wrote
this section, it was originally just in the global South,
but now it's everywhere. Gemini is free, Perplexit is three,
and metas LM is free. Whether dot com bubble was
(09:32):
made up of stupid businesses and the lack of fundamental
infrastructure to give most people the opportunity to access a
reliable Internet experience, Basically anybody can get reliable access to
Generative AI. Anyone claiming this is just like the early
days of the Internet is a fucking liar or a
fucking moron. Llms have now spread to every nook and
cranny of the Internet. Anybody can use one, anybody can
(09:54):
experience the so called power of AI. Users are not
sitting frothing at the mouth unable to access chet GPT
due to a lack of infrastructure. Nor is anybody saying, amen,
I can't access CLAW because I don't have a local
data center. They might be doing it because there's a
fucking rate limit, because Anthropic can't afford to run their services,
but that's not what this is about. Edward experiences are
(10:18):
not worse because these companies have a lack of access
to infrastructure or capital. They're worse because the underlying technology
of transformer based models is inherently limited, and in turn,
any company connected to these models is limited along with them.
Then we get to the economics of the AI bubble
and things begin to get more worrying. While the dot
com bubble rested on the back of companies like luciend, Cisco,
(10:41):
Nortel WorldCom Enron, and others, the AI bubble rests fundamentally
on one company in Video, and to a lesser extent,
the valuations of the remainder of the Magnificent seven Microsoft Amazon, Google, Meta, Apple,
and Tesla. Four of those companies Amazon, Microsoft, Google, and
Meta through to midiaries I'll get to in a future episode.
(11:02):
I think. Actually i'll explain in a second have spent
hundreds of billions of dollars on GPUs and their associated
infrastructure for reasons that none of them can seem to explain.
As in a side by the way. I will get
to this in an episode. I had to cut it
from the script just for length. It's already quite long.
There is a weird thing going on where Microsoft, Google, Meta, Amazon,
(11:23):
They don't buy their GPUs directly from Nvidia. They get
them through various Taiwanese holding companies like Fox Cotton Holding
companies is the wrong world. Manufacturers of server hardware and
search called like Honhai, who is Fox con, Wistron, Quantum Computing,
they order through Taiwan and then those sels are put
together and shipped to their data centers. This allows them
(11:46):
to hide how many GPUs they're buying from their investors
because guess what is quite a long anyway, when this
all collapses, we're also going to see a market contagion
that goes to Taiwan because all those Taiwanese companies are
booking revenue from selling these fucking servers anyway. Lots of
fun there, but let's keep going now. In Vidious revenue
(12:07):
is also predominantly eighty eight percent in its data center segment,
and it's customers of those who can afford at the
very least fifty to one hundred GPUs retailing at four
hundred grand or more for a pot of eight of them,
and you've require tens of thousands of dollars a networking
gear to go with them to make them turn on.
The Customers of those renting those GPUs are either AI
labs training or running inference for models, and their customers
(12:30):
are AI startups. The problem isn't so much that nobody
can afford a GPU, but that you can't get very
far with just one. You have to buy so many
of them. You need to build a big data center
around them, You need to get power to that data center,
and then you have the massive environmental concerns of well
running all that power. This naturally means that there are
really only two customers who can afford these chips at scale,
(12:52):
the Magnificent seven, who have all now begun to take
on debt after previously financing their GPU purchases with cash
flow and companies that raise them with companies meaning anybody
who wants to build a data center, an oracle who
had negative thirteen billion dollars in cash flow last quarter
and is steeped in debt to the point that bondholders
are suing them. We also have no idea if the
(13:13):
economics of renting GPUs actually makes sense, and based on
everything I've found, I'm not sure anybody renting them can
ever make a profit due to either or both the
upfront cost and debt necessary to pay it, and the
power intensive nature of providing AI compute. It is fundamentally
insane that we don't know for sure. It's so crazy.
How do we not know? How the fuck do we
(13:34):
not know that this is crazy? It's What we do
know is that the only company making any kind of
profit during the AI bubble appears to be in video
or Companies selling RAM, Microsoft, Google, Meta, and Amazon refuse
to share their actual AI revenues, and because people have
the brains of dogs, they have conflated revenue growth from
(13:56):
hyperscalis already existing segments like software and advertising, with growth
created by AI. In the dot com bubble, one could,
at the very least point to where a company was
making revenue, even if the answer was handing a dollar
to somebody and getting handed at a dollar back. People
bought and installed physical infrastructure, and that infrastructure was, albeit
a much lewer scale than the build out anticipated paid
(14:17):
for by the associated services. Companies got greedy, rushed to
expand in the way that was unnecessary, took on ruinous debt,
and suffered the consequences. This isn't what's happening in the
AI bubble. Consumers have no problem getting exposure to AI.
In fact, AI is breaking into every single device and
app that we have like an angry pervert with a knife.
(14:38):
While WorldCom wannabes like open Ai and Anthropic are whining
about not having enough compute, it's very clear they've got
more than enough to burp out a new model every
few months or drop copyright infringement machines on millions of
people at a moment's notice. The post bubble over build
of fiber left thousands of miles of dark I e
not connected to anything, cabling that took years to light.
(14:59):
But doing so, I had an obvious business use case
connecting people to the Internet and didn't require an entire
fucking data center and masses of power to do so.
To make matters worse, as I've hinted that the depreciation
of these GPUs is utterly brutal purple Kudrowski and I quote,
we are in a historically anomalous moment. Regardless of what
(15:19):
one thinks about the merits of AI or explosive data
center expansion, the scale and pasive capital deployment into a
rapidly depreciating technology is remarkable. These are not railroads. We
aren't building century long infrastructure. AI data centers are short lived,
aset intensive facilities, riding declining cost technology curves, requiring frequent
(15:39):
hardware replacement to preserve margins. Let me put it a
little simpler. Imagine if all of that fiber was useless
in five or six years at best. What if all
of that fiber could only be used to access a
small subset of websites. What if all of that fiber
required such massive amounts of power that it threatened rolling
(15:59):
blackouts of the East coast of America. That is the
scale of the apocalypse I am talking about, and I
am worried that people are not taking the problem. More seriously,
the demand for Invidio chips is fueled by hype, and
that hype has caused this company, and to a lesser extent,
the Magnificent Seven, to become a load bearing part of
the American stock market. An analysis from portfolio manager Don
(16:22):
Kee Jong from January twenty twenty five found that the
Magnificent Seven stocks accounted for forty seven point eight seven
percent of the Russell one thousand indexes returns in twenty
twenty four. And that's an index fund of the thousand
highest ranked stocks and the foot Sea Russell's Index. In
really simple terms, without the mostly vibes driven nature of
the Magnificent Seven's growth as none, if this is based
(16:43):
on anyone's actual revenues, the US stock market would be
in incredibly rough shape. Except unlike the dot com bubble,
most of these companies have taken on incredibly large amounts
of GPUs debt finance and operating leases and data centers
full of GPUs that can't be used for really much
of anything else. And because GPU is a guaranteed to depreciate,
each and every one of them will without fail have
(17:04):
to write down the value of upwards of one hundred
billion dollars of investments in the future, as these things
are eventually facing the recoverability test, which is when there's
a huge crash within any market sector and you have
to look at your assets and say, shit, will these
actually generate enough money? And this is going to happen
whether or not the AI bubble bursts. In Video is
(17:24):
on a yearly cycle of upgrades on their GPUs. Every
single year, every single GPU investment loses value, and to
make matts worse, takes fucking years to install these things,
so by the time they're there, your way in the past.
Even if the AI bubble doesn't burst, it's gonna The
US stock market has an unhealthy relationship within video, which
(17:46):
by this time next year will have to make over
ninety billion dollars a quarter to keep up with its
ridiculous fifty percent year every year growth, and by twenty
twenty eight and video will to keep its ridiculous valuation,
have to be making more than Apple, which makes about
foreign and sixteen billion dollars a year in revenue. In fact,
from my calculations, in video will have to be making
five hundred to six hundred billion dollars, which puts it
(18:08):
in the realm of Walmart. It can't happen. It can't happen.
Can't it can't happen, And to do that in video's
customers will continue having to be able to afford these GPUs, which,
as have established, are being paid out of debt because
AI services do not make a profim Even if AI
services take off and are useful in a way they've
(18:28):
never even remotely hinted it being, it is inevitable that
the debt and cash necessary to keep buying in video
GPUs runs out, and more than likely the revenues of
the Magnificent seven will stumble in growth before then, as
it becomes obvious that those GPUs are not providing any
meaningful revenue growth. The result, I fear, is that the
American stock market takes as shit the size of Iowa,
(18:51):
and due to the unique way that the tech industry functions,
the contagion will be global. I'll catch you tomorrow for
part three. I don't have a rosy or funny app
Every time I think of this stuff, I feel very
very sad. Well anyway, very optimistic.
Speaker 2 (19:06):
Peace.
Speaker 1 (19:06):
I'll catch you tomorrow.
Speaker 2 (19:16):
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(19:36):
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Speaker 1 (19:43):
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Speaker 2 (19:46):
Thank you so much for listening. Better Offline is a
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Speaker 1 (19:50):
For more from cool Zone Media, visit our website cool
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Zone Media. I'm d Zetron and this is better offline.
That's right, folks, We're back for the second part of
our series in the dot Com Bubble and why I
(00:23):
believe the AI Bubble could be much, much worse. While
the dot com bubble was a mixture of dodgy venture
capital deals and websites that could never turn a profit,
combined with a global mania around the interconnectivity of high
speed Internet companies, the AI bubble is one company selling
expensive aigpus, a bunch of companies building data sentence to
put them in, and a bunch of companies building shit
(00:44):
that runs on GPUs that only loses money and that
customers kind of fucking hate. I should also note that
a very important part of the story is venture capital's
lack of returns in the last few years, something I
covered in the Hitter financial Crisis last week, specifically in
parts two and three. In simple terms, AI startups now
make up more than half a venture investment, and I
(01:04):
believe that most of these stops will die because of
their horrible margins, no part to profitability, and products that
people really don't want to pay for its scale, and
when they die, they will leave venture capitalists stranded with
tons of dead equity at a time when they already
have trouble generating returns and thus raising money from their
limited partners. The result, I worry, will be gruesome. Venture
(01:25):
capitalists make their money through the fees they generate, which
are based on the value of their investments and the
returns they give their investors, which don't seem to be happening.
What do you think happens when they can't generate any
returns and their investments aren't worth anything. The answer is simple,
they won't have any way of raising more capital as
their limited partners won't fucking trust them. And to be clear,
(01:45):
these arswapes have cocked it up many years at a time.
Look at crypto, look at NFTs, look at ar VR, metaverse,
all of that, and all of this ridiculousness has happened
because of the ridiculous, ridiculous myths of AI, like just
the insatiable demand for AI compute and the made up
decline in the price of intelligence, which, by the way,
(02:07):
that last one I've talked about it, I swear to god,
I mentioned it in the Guardia, mentioned it everywhere. It
may be cheaper to pay for the tokens, but you
use more of them, so it's more expensive in the aggregate.
On top of that, it doesn't mean that the price
of intelligence for the model providers is going down. Jesus Christ,
I'm so tired of making this points. But in both cases,
(02:30):
these assumptions are convincing investors that it's time to invest
in data centers that only lose money because you assume
that the demand will be there, or in AI startups
to only lose money because you'll assume they magically stop
losing money somehow. And it turns out we do actually
have a historical comparison. The mania of the dot com
bubble was based on a misunderstanding of the scale of
(02:50):
the Internet at the time, rather than its actual potential.
Hundreds of billions of dollars were invested based on flimsy logic.
To quote researcher Justin Kohler. This continental rewiring was also
justified by another powerful myth that Internet traffic was doubling
every ninety days. This claim spread through analyst reports, burning
course and investor presentations like a particularly virulent meme. If true,
(03:15):
it meant the demand was growing exponentially, far out pacing
any conceivable supply, and that every new trench of fiber
would soon pay for itself many times over. And I
pause here to go, oh god, they're doing it again.
Back to the quote. But the mathematics were fiction. Network
researchers like Andrew Adlisco at AT and T, looking at
actual traffic data, found that US backbone traffic was doubling
(03:38):
roughly once a year, rapid growth, certainly, but nowhere near
the purported ninety day cycle. Meanwhile, advances in fiber technology
were making each strand exponentially more powerful. Dense wavelength division
multiplexing allowed dozens of signals to travel simultaneously down the
same line a different wavelengths of light, like multiple conversations
happening in different colours. While demand doubled annually, supply expanded
(04:02):
tenfold or more. Carriers buried the discrepancy under layers of
creative accounting that would have impressed medieval alchemists. First of all,
justin if you hear this, I fucking love that. That
was very fun. Second of all, to quote twin peaks,
it's happening again. Mania had taken hold based on very
flimsy logic. Economically speaking, this meant the telecoms companies, serve
(04:25):
a hardware companies, ISPs, construction firms, optical cable providers, wireless
technology companies, and basically anybody related to the business of
providing Internet access in any way saw a massive influx
of business to build capacity that didn't need to be
built yet. If you're in the business of selling services
to get people online, you were high on the hug,
you know, kind of like selling high bandwidth rem Similarly,
(04:49):
one could get a startup funded if you had a website,
or even take in public. One could raise debt to
build a nascent ISSP or a fiber network. The money
was flowing because people people weren't really really being thoughtful
about it. And as far as the dot com part
of the dot com bubble, the unsustainable websites, the problem
wasn't so much the industry but the businesses themselves, which
were hyped and dumped onto the public markets with little
(05:11):
regard for their long term health. The problem here is
relatively simple. These were bad companies that people ignored the
issues with because of and they quote the power of
the Internet and how it would somehow save them, which
which it didn't obviously had they been kept private. And
died in the dark. I don't think these companies would
have had the same reputation. I don't think we give
a fuck about pets dot com. I also don't think
(05:34):
they were really in accurate comparison to anything happening today.
While the valuations were ridiculous, the Globe's market cap was
at one point eight hundred and forty million dollars, the
scale of destruction caused by dot com startups was significantly smaller,
even in today's money. The economics were bad, but not
anywhere near as bad. For the first nine months of
(05:55):
nineteen ninety eight, the Globe made two point seven million
dollars in revenue and lost eleven point five million dollars,
largely due to trying to move into multiple different business
lines at once like voice over IP. And to be clear,
this company made money selling ads and also buying random companies.
Buying random companies was the thing that happened during the
dot com boom. Everybody fucking loved buying companies. You just
(06:16):
bought random. There was I think like Excite, bought at Home,
like there was the AT and T sort, the Aol
time Warner merger. So many stupid mergers, so little time. Nevertheless,
the economics of this shit show were quite complex. You
had companies raising money to do any website they could
think of, companies raising money to lay fiber, companies raising
(06:39):
money to found ISPs, all of which had multifaested layers
of physical and digital infrastructure that were quite ugh unbuilt.
I think is the term. It's tempting yet incorrect to
say the thing about AI. The similarity everybody points to
is that people doubted the Internet at the time, and
people really need to remember their fucking history. In two
thousand and only fifty two percent of Americans who were
(07:01):
using the Internet. By two thousand and three, the number
had only increased the sixty one percent per the World Bank.
In two thousand and five, only sixteen percent of the
world used the Internet, and in twenty twenty four the
number had increased to seventy one percent. Yet the real
difference is the access to high speed Internet. When the
Internet was connected via a fifth to six K modem,
access was at times charged by the minute, and even
(07:22):
if it was unlimited, it was always much much slower.
While we're used to connecting its speeds that make using
web based app near indistinguishable from using one on a computer.
Back in two thousand, two thousand and one or two
thousand and two, the average US Internet speed was at
best four hundred kilobits per second, or roughly fifty killer
bytes per second, compared to the average US Internet speed
today of other two hundred megabits per second or twenty
(07:45):
five megabytes per second. In simpler terms than the younger
members of the audience won't understand this, A website took
time to load in a way that feels almost impossible
to conceive if you didn't experience it at the time,
you had to make a commitment to God all website.
It was like you've browsed multiple tabs and fuck around
the different windows. You sat there and you waited a
(08:05):
little bit. Sometimes it came up quick and then another.
In fact, websites like Google were quite popular because they
were very clean, and the reason that them being clean
wasn't usability. It was the fact it loaded quickly, which
I guess would be usability either way. We've also had
dramatic improvements in web design and accessibility. The advent of
mobile browsing and the proliferation of widespread mobile and desktop
(08:28):
Internet access in the two thousands, we were at the
very early days of e commerce, and the weird irony
of the dot com bubble is that it was actually
pretty useful to lay millions of miles of fiber optic cable.
This is in no way, shape or form remotely comparable
to large language models GPUs or any nebulous VC spunk
(08:48):
around Generative AI. Global Internet access has never been higher
or cheaper, and for the most part, billions of people
(09:09):
can access the connection fast enough to use Generative AI.
There is very little stopping anyone from using an LM,
Chat GBT is free, chat GPT's cheaper ghost subscription has
now spread to the entire world. When I originally wrote
this section, it was originally just in the global South,
but now it's everywhere. Gemini is free, Perplexit is three,
and metas LM is free. Whether dot com bubble was
(09:32):
made up of stupid businesses and the lack of fundamental
infrastructure to give most people the opportunity to access a
reliable Internet experience, Basically anybody can get reliable access to
Generative AI. Anyone claiming this is just like the early
days of the Internet is a fucking liar or a
fucking moron. Llms have now spread to every nook and
cranny of the Internet. Anybody can use one, anybody can
(09:54):
experience the so called power of AI. Users are not
sitting frothing at the mouth unable to access chet GPT
due to a lack of infrastructure. Nor is anybody saying, amen,
I can't access CLAW because I don't have a local
data center. They might be doing it because there's a
fucking rate limit, because Anthropic can't afford to run their services,
but that's not what this is about. Edward experiences are
(10:18):
not worse because these companies have a lack of access
to infrastructure or capital. They're worse because the underlying technology
of transformer based models is inherently limited, and in turn,
any company connected to these models is limited along with them.
Then we get to the economics of the AI bubble
and things begin to get more worrying. While the dot
com bubble rested on the back of companies like luciend, Cisco,
(10:41):
Nortel WorldCom Enron, and others, the AI bubble rests fundamentally
on one company in Video, and to a lesser extent,
the valuations of the remainder of the Magnificent seven Microsoft Amazon, Google, Meta, Apple,
and Tesla. Four of those companies Amazon, Microsoft, Google, and
Meta through to midiaries I'll get to in a future episode.
(11:02):
I think. Actually i'll explain in a second have spent
hundreds of billions of dollars on GPUs and their associated
infrastructure for reasons that none of them can seem to explain.
As in a side by the way. I will get
to this in an episode. I had to cut it
from the script just for length. It's already quite long.
There is a weird thing going on where Microsoft, Google, Meta, Amazon,
(11:23):
They don't buy their GPUs directly from Nvidia. They get
them through various Taiwanese holding companies like Fox Cotton Holding
companies is the wrong world. Manufacturers of server hardware and
search called like Honhai, who is Fox con, Wistron, Quantum Computing,
they order through Taiwan and then those sels are put
together and shipped to their data centers. This allows them
(11:46):
to hide how many GPUs they're buying from their investors
because guess what is quite a long anyway, when this
all collapses, we're also going to see a market contagion
that goes to Taiwan because all those Taiwanese companies are
booking revenue from selling these fucking servers anyway. Lots of
fun there, but let's keep going now. In Vidious revenue
(12:07):
is also predominantly eighty eight percent in its data center segment,
and it's customers of those who can afford at the
very least fifty to one hundred GPUs retailing at four
hundred grand or more for a pot of eight of them,
and you've require tens of thousands of dollars a networking
gear to go with them to make them turn on.
The Customers of those renting those GPUs are either AI
labs training or running inference for models, and their customers
(12:30):
are AI startups. The problem isn't so much that nobody
can afford a GPU, but that you can't get very
far with just one. You have to buy so many
of them. You need to build a big data center
around them, You need to get power to that data center,
and then you have the massive environmental concerns of well
running all that power. This naturally means that there are
really only two customers who can afford these chips at scale,
(12:52):
the Magnificent seven, who have all now begun to take
on debt after previously financing their GPU purchases with cash
flow and companies that raise them with companies meaning anybody
who wants to build a data center, an oracle who
had negative thirteen billion dollars in cash flow last quarter
and is steeped in debt to the point that bondholders
are suing them. We also have no idea if the
(13:13):
economics of renting GPUs actually makes sense, and based on
everything I've found, I'm not sure anybody renting them can
ever make a profit due to either or both the
upfront cost and debt necessary to pay it, and the
power intensive nature of providing AI compute. It is fundamentally
insane that we don't know for sure. It's so crazy.
How do we not know? How the fuck do we
(13:34):
not know that this is crazy? It's What we do
know is that the only company making any kind of
profit during the AI bubble appears to be in video
or Companies selling RAM, Microsoft, Google, Meta, and Amazon refuse
to share their actual AI revenues, and because people have
the brains of dogs, they have conflated revenue growth from
(13:56):
hyperscalis already existing segments like software and advertising, with growth
created by AI. In the dot com bubble, one could,
at the very least point to where a company was
making revenue, even if the answer was handing a dollar
to somebody and getting handed at a dollar back. People
bought and installed physical infrastructure, and that infrastructure was, albeit
a much lewer scale than the build out anticipated paid
(14:17):
for by the associated services. Companies got greedy, rushed to
expand in the way that was unnecessary, took on ruinous debt,
and suffered the consequences. This isn't what's happening in the
AI bubble. Consumers have no problem getting exposure to AI.
In fact, AI is breaking into every single device and
app that we have like an angry pervert with a knife.
(14:38):
While WorldCom wannabes like open Ai and Anthropic are whining
about not having enough compute, it's very clear they've got
more than enough to burp out a new model every
few months or drop copyright infringement machines on millions of
people at a moment's notice. The post bubble over build
of fiber left thousands of miles of dark I e
not connected to anything, cabling that took years to light.
(14:59):
But doing so, I had an obvious business use case
connecting people to the Internet and didn't require an entire
fucking data center and masses of power to do so.
To make matters worse, as I've hinted that the depreciation
of these GPUs is utterly brutal purple Kudrowski and I quote,
we are in a historically anomalous moment. Regardless of what
(15:19):
one thinks about the merits of AI or explosive data
center expansion, the scale and pasive capital deployment into a
rapidly depreciating technology is remarkable. These are not railroads. We
aren't building century long infrastructure. AI data centers are short lived,
aset intensive facilities, riding declining cost technology curves, requiring frequent
(15:39):
hardware replacement to preserve margins. Let me put it a
little simpler. Imagine if all of that fiber was useless
in five or six years at best. What if all
of that fiber could only be used to access a
small subset of websites. What if all of that fiber
required such massive amounts of power that it threatened rolling
(15:59):
blackouts of the East coast of America. That is the
scale of the apocalypse I am talking about, and I
am worried that people are not taking the problem. More seriously,
the demand for Invidio chips is fueled by hype, and
that hype has caused this company, and to a lesser extent,
the Magnificent Seven, to become a load bearing part of
the American stock market. An analysis from portfolio manager Don
(16:22):
Kee Jong from January twenty twenty five found that the
Magnificent Seven stocks accounted for forty seven point eight seven
percent of the Russell one thousand indexes returns in twenty
twenty four. And that's an index fund of the thousand
highest ranked stocks and the foot Sea Russell's Index. In
really simple terms, without the mostly vibes driven nature of
the Magnificent Seven's growth as none, if this is based
(16:43):
on anyone's actual revenues, the US stock market would be
in incredibly rough shape. Except unlike the dot com bubble,
most of these companies have taken on incredibly large amounts
of GPUs debt finance and operating leases and data centers
full of GPUs that can't be used for really much
of anything else. And because GPU is a guaranteed to depreciate,
each and every one of them will without fail have
(17:04):
to write down the value of upwards of one hundred
billion dollars of investments in the future, as these things
are eventually facing the recoverability test, which is when there's
a huge crash within any market sector and you have
to look at your assets and say, shit, will these
actually generate enough money? And this is going to happen
whether or not the AI bubble bursts. In Video is
(17:24):
on a yearly cycle of upgrades on their GPUs. Every
single year, every single GPU investment loses value, and to
make matts worse, takes fucking years to install these things,
so by the time they're there, your way in the past.
Even if the AI bubble doesn't burst, it's gonna The
US stock market has an unhealthy relationship within video, which
(17:46):
by this time next year will have to make over
ninety billion dollars a quarter to keep up with its
ridiculous fifty percent year every year growth, and by twenty
twenty eight and video will to keep its ridiculous valuation,
have to be making more than Apple, which makes about
foreign and sixteen billion dollars a year in revenue. In fact,
from my calculations, in video will have to be making
five hundred to six hundred billion dollars, which puts it
(18:08):
in the realm of Walmart. It can't happen. It can't happen.
Can't it can't happen, And to do that in video's
customers will continue having to be able to afford these GPUs, which,
as have established, are being paid out of debt because
AI services do not make a profim Even if AI
services take off and are useful in a way they've
(18:28):
never even remotely hinted it being, it is inevitable that
the debt and cash necessary to keep buying in video
GPUs runs out, and more than likely the revenues of
the Magnificent seven will stumble in growth before then, as
it becomes obvious that those GPUs are not providing any
meaningful revenue growth. The result, I fear, is that the
American stock market takes as shit the size of Iowa,
(18:51):
and due to the unique way that the tech industry functions,
the contagion will be global. I'll catch you tomorrow for
part three. I don't have a rosy or funny app
Every time I think of this stuff, I feel very
very sad. Well anyway, very optimistic.
Speaker 2 (19:06):
Peace.
Speaker 1 (19:06):
I'll catch you tomorrow.
Speaker 2 (19:16):
Thank you for listening to better Offline The editor and
composer of the Better Offline theme song is Matasowski. You
can check out more of his music and audio projects
at Mattasowski dot com, m A T T O s
O W s ki dot com. You can email me
at easy at Better offline dot com or visit Better
Offline dot com to find more podcast links and of course,
(19:36):
my newsletter. I also really recommend you go to chat
dot Where's youreed dot at to visit the discord, and
go to our slash.
Speaker 1 (19:43):
Better Offline to check out our reddit.
Speaker 2 (19:46):
Thank you so much for listening. Better Offline is a
production of cool Zone Media.
Speaker 1 (19:50):
For more from cool Zone Media, visit our website cool
Zonemedia dot com, or check us out on the iHeartRadio app,
Apple Podcasts, or wherever you get your podcasts.
Host
Ed Zitron
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