Welcome back to the Deep Dive. If you've been
watching the headlines at all, you know the biggest
story right now. I mean, maybe the biggest story
of 2025 is the sheer, just breathtaking flow
of capital into artificial intelligence. It's
everywhere. Everywhere. We're talking trillions
of dollars being funneled into a really concentrated
group of tech firms all building this infrastructure
for our AI future. The momentum, it just feels
unstoppable. It does. And that momentum is precisely
where our deep dive has to begin. The sources
you sent over really highlight this powerful
central paradox. OK. On the one hand, you have
this rapid growth, this unprecedented investment
sparking just mass optimism. But on the other,
a lot of established financial experts are Well,
they're sounding an alarm. Alarm about what exactly?
They're warning that all this growth is masking
some pretty significant systemic risks, hidden
vulnerabilities that could challenge the stability
of the whole market. That's fascinating. So the
risk isn't just about whether the tech itself
works, but how the financial system is, you know,
handling all this money. Our mission today is
to take a really detailed look at the AI market
landscape, maybe identify some historical parallels
that tell us where we might be in the cycle,
and most importantly, pull back the curtain on
the fragility behind all the hype. And we'll
be using your research as our map. Let's do it.
I think we have to unpack the scale first, because
the numbers themselves are just... They're staggering.
And they really lay the groundwork for understanding
the risk. Absolutely. When we talk about financial
commitment, we are way past the point of casual
investing. Oh, yeah. The projection is that US
AI -related investment is set to exceed $100
billion this year alone. And that's just the
US. If you look globally, some estimates are
suggesting we could be approaching $200 billion
by the end of the year. That kind of concentrated
capital is. It's just so rare. It is rare, but,
you know, the total dollar amount, while it's
eye -catching, it's actually secondary to how
that money is circulating. OK, what do you mean?
This colossal investment isn't discussed widely.
It's flowing through a small, really tightly
controlled ecosystem. And that introduces what
our sources are calling concentration risk. Concentration
risk. And that's the foundational problem. It
leads us directly to this concept of closed loop
spending. Closed loop spending. When you hear
a term like that in finance, you instinctively
know it's probably not a good thing. How does
that loop actually operate? Think of it as a
really specific interconnected network. a club,
basically, where money is only exchanged between
the members. Okay. Give me an example. Sure.
A major venture capital arm of, say, a big AI
software firm gives financing to a specialized
chip startup. That startup then uses that funding
to buy advanced chips exclusively from the original
parent company. Ah, so the money never actually
leaves the orbit of this small group of firms.
Exactly. Company A gives capital to Company B,
and Company B turns right around and uses it
to buy Company A's products. It's a circular
mechanism. And that artificially inflates asset
valuations. It has to, because the spending isn't
being validated by organic third -party demand
from the real economy. It's internal capital
driving the recorded price and what looks like
revenue growth. Which makes it almost impossible
to figure out the true value of the technology
if and when that cycle eventually breaks. It
does. And the consequence of this closed loop
is this rapid, extreme concentration of risk
across the whole industry. These firms aren't
just partners. They're financially interwoven.
So if one of them gets into trouble, if sentiment
shifts or if regulators land heavily on just
one major player, the dependency in that loop
means the contagion will be swift and frankly
pretty painful for the entire sector. And we
know regulators are watching this like a hawk.
The Financial Stability Oversight Council, they've
explicitly flagged vulnerabilities tied to this
exact boom. But what really stood out to me was
the observation that markets are showing markedly
increased correlations. That phrase is a five
alarm fire bell for systemic risk. It sounds
like it. I mean, historically, you mitigated
risk with diversification. Yeah. Right. You held
stocks in different sectors, energy, health care,
tech. And if one went down, the others might
be stable or even go up because they had different
risk drivers. Precisely. But when correlations
become markedly increased, it means assets that
should move independently are now all moving
in lockstep. It's a direct result of this closed
loop financing. So diversification isn't really
a safety net anymore? The refuge is dramatically
shrinking, especially if your portfolio is heavy
in these AI exposed sectors. The factors driving
one company's price are the same factors driving
all of them. This level of financial fervor,
it just naturally makes you think about financial
history. I mean, have we seen this kind of setup
before? Oh, we absolutely have. And to analyze
it... We really need the framework from the economist
Charles Kindleberger. He outlined the classic
sequence of a financial mania. The five phases.
Right. Displacement, euphoria, mania, distress,
and finally, revulsion. And if we're looking
at the current AI moment through that lens, where
do we land? Well, the displacement was the breakthrough
of large language models, of generative AI itself.
The euphoria was that first burst of capital
back in 2023. But according to historians like
Neil Ferguson, the current AI market is now,
and I'm quoting, firmly within the media phase.
That is a critical label. But wait, I have to
push back just a little on that. Unlike, say,
the Dutch tulip mania or even the dot com era.
AI produces real, tangible efficiency gains for
businesses right now. It's transforming processes
today. Doesn't that genuine tech displacement
justify some of this valuation? Does the mania
comparison really hold up? That's the essential
difficult question, isn't it? Yeah. Separating
genuine innovation from financial excess. And
you're right, the technology is undeniably transformative.
But mania isn't defined by the technology's quality.
It's defined by investor behavior. Exactly. In
the mania phase, you see this excessive optimism
where spectacular future revenues are treated
as near certainties today. It results in valuations
that demand decades of absolutely perfect execution.
So the behavior is just outrunning the balance
sheet. It is. The investment enthusiasm consistently
outstrips the underlying measurable fundamentals.
It's investment based on the dream, not the current
proven earnings. We saw the same psychology in
the 1920s stock bubble and the 90s tech surge,
that feeling that the rules have changed forever.
That this time is different. That belief is the
defining psychological trap of the mania phase.
And we're seeing specific vivid markers of it
today. We are. The source material points to
things like advanced chip orders being placed
years ahead of when a customer could possibly
use them, or near -weekly partnership announcements
that seem designed more for market headlines
than for immediate functional value. And you
see entire legacy sectors being forced to realign
just so they can tell investors they're part
of the AI theme. It's that pressure to just be
seen as participating that defines it. Yes. And
here's where the paradox gets so dangerous. History
shows the mania phase feels the safest while
you're in it because the market's rising. Everyone
else is getting rich. The riskiest choice feels
like stepping away. And that illusion of safety.
is the core of the fragility we have to recognize.
The sheer narrow concentration, everyone piling
into the same few stocks, it just. mathematically
increases the systemic fragility of the markets.
It's like everyone building their house on the
same increasingly narrow foundation. The whole
neighborhood is vulnerable to the same earthquake.
That's a perfect analogy. And when you combine
that with the closed -loop financing we talked
about, where firms are tethered together, you
create these powerful feedback loops. So one
bad announcement from one company. And the entire
intertwined sector immediately feels distress.
This is why these soaring AI indices, while they
give off this sense of you know, seeming stability,
are actually masking vulnerabilities that could
trigger rapid violent adjustments if that investor
sentiment subtly changes. Which brings us from
structural risk to behavioral risk. You call
this action bias. And this affects everyone,
from a CEO deciding on R &D spending to an individual
investor trying to manage their savings. Action
bias is that powerful compulsion to act, even
when the rational choice might be to wait or
diversify or even retreat. In this context, it
means corporate execs and retail investors feel
this intense pressure social competitive to maintain
maximum exposure to the winning theme, which
right now is AI. Even when the risks are becoming
pretty obvious. Even then. The fear of missing
out, you know, it just overrides basic risk management.
Which is what makes the inevitable correction
so much worse. That behavioral pressure intensifies
the volatility. When market reality finally hits
disappointing earnings or regulatory action,
whatever it is, the adjustment is amplified because
so many people felt they had to be in this one
single theme. The rush for the exit is just incredibly
crowded. It's a really compelling case for the
fragility of it all. So against this backdrop
of concentration and behavioral pressure, prudent
planning means you have to look outside the dominant
tech cycle for some stability. That forces us
to shift focus dramatically. We have to move
away from these high beta tech assets to assets
the sources site as potentially providing that
stability. Specifically, long -standing monetary
metals. Gold and silver. Contrasting assets in
almost every way. On every functional way. Yeah.
And that contrast matters so much right now.
Why specifically? What makes them so different
in this context? Because they operate completely
independently of the current tech cycles and
those circular financing schemes we talked about.
Their value is driven by things like monetary
policy, inflation, geopolitical stability, not
the quarterly earnings of a chip maker. They're
non -correlated. Genuinely non -correlated. And
critically, they carry virtually no counterparty
risk, which is a key requirement for safety when
you think the system itself might be fragile.
And the data suggests this isn't just... a hypothetical
flight to safety, there are structural trends
in these assets that started even before the
current AIP. Absolutely. The research highlights
some specific data here. Gold, for instance,
has broken out of what was an 11 -year relative
performance base against equities. OK, let's
just clarify that term for everyone listening.
An 11 -year relative performance base breakout.
That sounds technical, but what does it actually
mean for investor confidence? It means that for
over a decade, gold's performance compared to,
say, the S &P 500 was stuck in a defined range.
Breaking out of that range suggests the market's
long -term calculus of risk and reward has fundamentally
changed. So investors are basically saying that
gold stability is more valuable today than it
has been for the last 10 years. Exactly. It indicates
a deep -seated loss of confidence in the sustained
stability of these high -growth, concentrated
equity markets. And what about silver? It's always
a bit trickier with its dual role as a monetary
metal but also with huge industrial demand. Well,
silver is poised for some more momentum gains.
And that dual nature actually makes it more resilient.
It gets the safety hedge benefit like gold. But
it's huge industrial demand for solar panels,
electronics. It supports its value, even if financial
markets get volatile. It has a diversified demand
base, which makes it a powerful anchor. So we've
mapped the concentration. We've seen the historical
parallels. We've identified some stability anchors.
What does this all mean for the big picture?
Let's start with policymakers. What a challenge
they must be facing. It's monumental. For them,
the rapid spread of AI demands refined governance,
regulatory transparency, and just more robust
risk management. The challenge is mitigating
this systemic risk, avoiding a collapse rooted
in one sector without stifling the incredible
innovation AI promises. A tough balancing act.
It's historically very difficult to achieve.
And for you, for the individual learner trying
to navigate this landscape day to day. The main
takeaway is just the absolute importance of enhancing
your financial literacy around this. This dissonance
between market narrative and economic reality.
The story versus the numbers. Right. The narrative
is exhilarating. The reality is that the underlying
fundamentals are strained by closed -loop financing
and concentration. You have to maintain critical
awareness of these themes and understand financial
cycles, recognizing the behaviors of a mania
phase as it's happening. So here's the final
synthesis from your sources. The AI boom is a
watershed moment. It's extraordinary capital
flow. It's transformative technology. But, and
this is the critical part, This momentum conceals
a significant fragility steeped in narrow concentration
and exuberant, often irrational, sentiment. And
the need to value differentiated assets that
can provide stability against corrections has,
I think, rarely been higher. The traditional
anchors, gold and silver, They stand out because
they reflect these enduring qualities of diversification
and safety that the current tech market just
cannot offer. This deep dive has laid bare the
historical precedence and the structural risks
we're facing. But I want to leave you with one
final thought. It ties the history to the behavioral
challenge right now. If history consistently
shows that the mania phase feels the least risky
while you are fully immersed in it, how do you
personally distinguish between genuine technological
displacement that justifies massive valuations
and the sheer beha - behavioral pressure of action
bias compelling you to follow the crowd right
up to the cliff's edge. That's the essential
self -reflective question every investor has
to answer right now. That is a profound thought
to end on. Thank you for sharing your sources
and letting us dive deep into the risks behind
the AI boom. We'll see you next time on the Deep
Dive.