Intro music. On March 2nd, 2026, over $7 billion
quietly vanished into one narrow, highly specific
corner of the tech supply chain. No flashy AI
startup. No new LLM. Just glass, light, and,
uh... Welcome to your custom deep dive. Today,
we are exploring a fundamental infrastructure
shift happening right now beneath the surface
of the AI boom. We're looking at a definitive
March 2026 guide. detailing the massive pivot
away from traditional copper wiring. Right. First,
we'll unpack the physical limits of what engineers
are calling the copper wall. And next, we'll
explore the mind bending, elegant solution of
silicon photonics. Finally, we'll break down
the three layer framework of companies actually
building this new light speed ecosystem. So let's
dig in. The best place to start is tracking that
massive capital flight because, you know, money
of that magnitude does not move by accident.
Absolutely not. In early March, NVIDIA quietly
took $4 billion and split it evenly between two
relatively unknown hardware companies, Coherent
and Lumentum. $2 billion each. Wow. And this
wasn't speculative venture capital. These were
backed by massive multi -year purchase commitments.
Yeah, and Marvell Technology made similar aggressive
moves at the exact same time. They spent nearly
$3 .8 billion acquiring optical companies. I
mean, they closed a $3 .25 billion deal just
for a single startup called Celestial AI. And
then threw in another $540 million deal for a
networking company. Right. When you see the most
dominant players in artificial intelligence aggressively
locking up the supply chain for a specific type
of hardware, it points to a much deeper shift.
It really does. This capital flight marks the
definitive end of the copper era in high performance
computing. The industry hasn't hit a software
bottleneck. It has hit a hard physical limit
of nature. The copper wall. Yeah. Let's unpack
the mechanics of this wall because this is where
the physics get incredibly fascinating. Let's
do it. The bottleneck holding back the next generation
of AI is not actually computing power anymore.
We know how to make faster chips. The problem
is how fast those chips can talk to each other.
Every modern AI data center is essentially a
vast, sprawling city of silicon. You have tens
of thousands of GTUs constantly exchanging data
every single second to train these massive models.
And right now, the speed of that data transfer
is pushing toward a critical threshold, 1 .6
terabits per second, or TBPS. Okay. At that specific
speed, traditional copper cables literally begin
to break down. And they don't fail gracefully,
right? Or in just one way? No, not at all. They
fail in three distinct ways all at once. Engineers
call it the three -threat failure. heat, power,
and signal quality. I was thinking about this
earlier. It's like trying to force a high -pressure
fire hose of data through a garden hose made
of copper. Exactly. But worse, because of electrical
resistance, the water in this hose isn't just
backing up. It is boiling. Yeah, the friction
of the electrons moving at 1 .6 terabits physically
threatens to melt the hardware. And the power
demands explode non -linearly. The signal just
degrades into pure static noise. This is not
a software bug we can patch with a clever algorithm.
It is a hard limit of physics. It all comes down
to how electrons travel through a conductor.
At lower speeds, copper is fantastic. It's cheap.
It's malleable. It's reliable. Sure. But as you
push data at high frequencies, you encounter
phenomena like... The skin effect. The skin effect.
Yeah. The electrons actually get pushed to the
outer edges of the copper wire, which minimizes
the usable area for the current. Oh, I see. That
drastically jacks up the electrical resistance.
And that resistance generates massive, unmanageable
heat. Which brings up an obvious question. Data
centers already consume gargantuan amounts of
electricity. Oh, massive amounts. Some of them
draw over 100 megawatts, which is enough to power
a small city. So could this heat issue simply
be solved by... building radically better liquid
cooling systems instead of completely abandoning
copper. I mean, it sounds like a logical brute
force fix. Yeah. But the power usage at 1 .6
TBP is spikes exponentially, not linearly. Wait,
exponentially? Yeah. If you double the speed,
you don't just double the heat, it multiplies.
Pumping more extreme cooling into the system
requires even more power to run the chillers
and pumps. Right. Eventually, the power required
just to cool the copper exceeds the power used
to run the AI calculations. It becomes physically
and economically unviable. So we literally cannot
out -cool the fundamental laws of thermodynamics.
We really can't. And even if you could somehow
keep it cold, you still face the third threat,
signal quality. Right. At 1 .6 TBps, electrical
signals degrade over incredibly short distances.
A copper connection that is just a few inches
long starts losing clarity. The ones and zeros
blur together into noise. Exactly. To fix that,
the network has to constantly run error correction
algorithms and resend dropped packets of data.
Which creates latency. Which entirely defeats
the purpose of buying faster, more expensive
hardware. Right. So since physics is breaking
copper, we clearly need a new medium. We have
to bypass electrical resistance altogether. And
the elegant, almost science fiction solution
to this is light. We are taking the electrical
signals and replacing them with beams of light.
We're swapping out heavy friction bound electrons
for weightless. frictionless photons. Yeah, that's
the core concept behind silicon photonics. I
have to admit, I still struggle to wrap my head
around light replacing electricity at a microscopic
packaging level. It's wild, isn't it? It really
is. I understand fiber optics running under the
ocean to connect continents, but shrinking that
concept down to a microscopic scale inside a
single computer chip feels wild. It is a profound
feat of engineering. Instead of using tiny copper
wires to connect the processors, the History
is transitioning to wave guides. Let's define
that quickly for the listener. Wave guides, tiny
glass pathways etched into silicon chips that
steer light beams. Yeah. That is exactly it.
They are microscopic glass channels. Yeah. And
because light behaves completely differently
than electricity, it doesn't suffer from that
electrical resistance we just talked about. Which
completely eliminates the massive heat generation
problem. Right. Photons don't cause friction
the way electrons do. It also requires significantly
less energy to travel over the same physical
distance. How much less? By moving to silicon
photonics, you get roughly 3 to 3 .5 times better
power efficiency per individual interconnect
link. Just to visualize the scale of that, a
standard modern AI data center has somewhere
between 40 ,000 and 50 ,000 interconnect links.
Whoa! Imagine 50 ,000 interconnects in a single
data center suddenly running three times more
efficiently. It completely reshapes the grid.
You're talking about a structural transformation
of how computing centers are built from the ground
up. Absolutely. The market projections are already
pricing in this massive structural shift. Yeah.
In 2025, the silicon photonics market was sitting
at roughly $2 .65 billion. But because of this
copper wall, it's projected to reach $9 .65 billion
by 2030. Growing at nearly 30 % annually. And
some of the more aggressive forecasts even push
it toward $28 billion by 2034. It is an absolute
tidal wave of capital. But replacing every copper
wire with a glass waveguide is a colossal undertaking.
Which raises a massive logistical question. If
we are completely abandoning copper for light,
does using light mean we have to invent entirely
new manufacturing processes and build new factories
from scratch? And that is the true underlying
genius of this technological shift. We don't
need to reinvent the wheel. We don't. No. The
genius is using the exact same silicon chip manufacturing
processes that the semiconductor industry has
ruthlessly perfected over the last 40 years.
Oh, wow. Yeah, we're just repurposing those billion
dollar machines. We're hacking silicon factories
to print glass light paths instead of copper
wires. Sponsor. That is the magic of it. It allows
this incredibly advanced transition to scale
up rapidly without needing to spend trillions
of dollars building a whole new type of industrial
supply chain. OK, now that we understand the
core technology and why the physics of copper
are forcing this shift, we need a map. Right.
We have to navigate this emerging market intelligently
rather than just throwing darts at tech stocks.
Exactly. The sources outline a fantastic mental
model for this called the three -layer framework.
This framework helps us categorize the ecosystem.
We start at the foundation, which is the base
layer. These are the mega caps. The trillion
dollar giants dictating the architecture of the
shift. For them, photonics is just one necessary
component of a much larger supercomputing business.
First up in that base layer is NVIDIA. They aren't
just a chip designer anymore, right? No, they're
the primary architect of this entire transition.
NVIDIA sells entire rack -scale supercomputing
systems now. It's not just a GPU you plug into
a motherboard. Right. Their new Vera Rubin platform,
which starts shipping in the second half of 2026,
is a perfect example. It packs 72 massive GPUs
into a single server rack. 72? That's insane.
It holds 1 .3 million individual components per
system. If you tried to wire that entirely with
copper, it would incinerate itself. So Vera Rubin
integrates silicon photonics natively. Exactly.
To support that, their new Spectrum 6 switches
are delivering five times better power efficiency
than traditional networking hardware. And their
SuperNex are running at exactly 1 .6 TBPS. That
speed is not a coincidence. Nope. It is right
at the precise threshold where copper networking
breaks down, forcing their customers to adopt
the optical standard. Next in the base layer
is Broadcom. And they're taking a slightly different
approach. They're the pioneer of what is known
as co -packaging. Co -packaging. So Broadcom
embeds the optics directly onto the networking
chip itself. Right. Just to clarify, usually
the optical laser and the processor are separate
components, right? Right. And data has to travel
across the board to get from one to the other.
Exactly. But by co -packaging them, Broadcom
drastically shortens the physical data paths.
It cuts power consumption and dramatically improves
signal clarity. Because the data barely has to
travel before it turns into light. Yeah. Then
we have Cisco. They are making the enterprise
backbone play. People often think of Cisco as
old -school networking. Maybe a bit boring. Right.
But that actually puts them in a dominant position.
Every enterprise data center, banks, hospitals,
logistics hubs will eventually have to replace
their aging copper infrastructure with optical
interconnects. And Cisco already owns those relationships.
They acquired an optics pioneer called Acacia
a few years ago. And now they're manufacturing
800 GBP silicon photonic transceivers to feed
that enterprise demand. Finally, we have the
controversial wild card of the base layer, Intel.
Intel is fascinating here. They actually have
25 years of quiet research and development in
photonics. 25 years. They've already shipped
over 8 million photonic chips to date. Wow. Their
new optical compute interconnect or OCI chiplet
is highly advanced. It runs at four TBPs bidirectionally.
And here's the insane metric. It consumes just
five picojoules per bit of data transferred.
Let's contextualize that because picojoules are
hard to grasp. Right. A picojoule is one trillionth
of a joule. Traditional pluggable optical modules
consume about 15 picajoules per bit. So Intel's
chiplet represents a massive 3x power advantage
in an industry where power is the ultimate bottleneck.
But Intel has obviously faced real public, corporate,
and execution struggles recently. Yeah, they
have. Does their current corporate turmoil make
their 25 -year head start in photonics irrelevant?
Well, the execution risk for Intel is admittedly
quite high right now. The market is highly skeptical.
Understandably. But if you look strictly at their
assets, Intel is uniquely positioned globally.
They are the only major foundry on the planet
right now, offering optics -based manufacturing
to external customers at that specific scale.
If Intel executes their manufacturing advantage,
their upside is much bigger than expected. Precisely.
And talking about manufacturing perfectly transitions
us up. a level to the middle layer these are
the foundries and the manufacturers right because
the mega caps like nvidia and broadcom design
the grand architecture but they don't actually
own the machines that build the chips someone
has to physically etch the glass into the silicon
This layer is crucial because it reveals the
actual physical constraints of the market. And
we got a huge signal about this on March 18th,
2026. TSMC, Taiwan's semiconductor manufacturing
company, made a major announcement. Yeah, they
confirmed their dedicated COUPN manufacturing
line is at absolute full capacity. This line
is specifically building 1 .6T optical modules
for companies like NVIDIA and Broadcom. TSMC
is arguably the most important foundry in the
world. Without a doubt. When they dedicate a
massive production line to a new technology and
immediately sell out of capacity, it proves that
photonics is officially an infrastructure standard.
It is no longer an R &D experiment. Exactly.
We also have tower semiconductor in this middle
layer. They are the number one specialist foundry
in the world for this tech. They focus purely
on fabricating silicon photonics on silicon wafers.
Yeah. They have a direct partnership with NVIDIA,
and the demand is so high that 70 % of their
new manufacturing capacity is already reserved
through 2028. Customers are making massive non
-refundable prepayments just to secure a physical
space on the assembly line. Then there is GlobalFoundries.
They are playing the scale game. Global Foundries
uniquely integrates the optical chip and the
full module together. Right. They do the entire
fabrication in one single continuous process.
That end -to -end capability is incredibly hard
to replicate at scale, and it lowers the cost
per unit. They're aiming to turn this into a
$1 billion annual run rate by 2028. And we absolutely
cannot forget about Fabernae. This might be the
most interesting company in the entire document.
They are a hidden beneficiary based in Thailand.
Fabernae focuses purely on high -precision manufacturing.
Specifically, they specialize in submicron alignment.
Which sounds technical, but if you think about
it, it's wild. You're trying to perfectly align
a microscopic laser beam so it fires directly
into a microscopic glass pathway. It's like threading
a microscopic needle during an earthquake. Exactly.
If the alignment is off by even a fraction of
a hair, the light hits the silicon instead of
the glass, the data drops, and a $100 ,000 server
rack crashes. It is incredibly difficult, and
very few companies in the world can do it reliably
at scale. Right. Fabernae runs over 2 million
square feet of factory space dedicated to this.
And here is the kicker. They manufacture these
highly sensitive components for both coherent
and momentum. Those are the two competitors that
NVIDIA just gave $2 billion each. Wait, if Coherent
and Lumentum are technically competing for market
share, but Fabrinet is manufacturing the components
for both of them, why should an investor or an
observer even care about picking the flashy chip
designers? Because Fabrinet captures the spending
across the entire ecosystem without taking on
the design risk. Right. They don't need to pick
which specific architectural design wins the
war. The capital flows straight through their
clean rooms regardless. They sell the picks and
shovels. They win regardless of whose design
dominates. That is the perfect way to look at
it. And that finally brings us to the top layer.
This is the roof of the house, the pure play
photonics companies. These are the high risk,
high reward specialists that are actually designing
and building the specific hardware components
that go into the mega cap architectures. Coherent
is the vertically integrated giant in this layer.
They build absolutely everything from the raw
laser chip up to the final transceiver module.
They keep the entire process in house, which
gives them immense control over quality and margins.
They are the ones who secured that massive $2
billion multi -year deal from Nvidia we mentioned
at the start. It was the largest single deal
in company history. And yet, even with that growth,
their peg ratio sits around 1 .1 right now. For
you listening, a peg ratio compares a company's
stock price to its expected earnings growth.
A peg around 1 essentially means the stock is
fairly valued, maybe slightly undervalued, compared
to the hyperinflated AI software stocks. Right.
Then we have lumentum. They are the laser supplier
to everyone. This is a vital physical constraint
we haven't touched on yet. Silicon, the material
the chips are made of, is what physicists call
an indirect bandgap material. In plain English,
silicon cannot generate light on its own. Right.
Every single silicon photonics chip, no matter
how advanced, needs an external laser source
to provide the actual light. So even Lumentum's
direct competitors often have to buy Lumentum's
lasers to power their own modules. No matter
whose broader design wins out, Lumentum still
gets paid for the light source. Exactly. They
just lock in a massive NVIDIA supply commitment
as well. And they are currently trading at a
very attractive peg ratio of 0 .61. Meaning the
market is severely underpricing their future
growth. Yeah. Finally. We arrive at Marvell technology.
They are the data interpreter and lately an incredibly
aggressive serial acquirer. Marvell holds an
estimated 50 % market share in digital signal
processing or DSP. DSP chips are the unsung heroes
of this entire revolution. Right, because when
a beam of light speeds through the glass waveguide
and exits the photonic chip, it is still just
an analog light wave. It must be rapidly translated
back into digital data. The ones and zeros so
the actual GPU can process it. But interpreting
data isn't enough for them anymore. They just
spent $3 .25 billion to acquire a company called
Celestial AI. You have to look at Celestial's
specific performance specs. Celestial is pioneering
something called a photonic fabric. A photonic
fabric. Yeah. They use light not just to connect
servers across a room, but to connect computing
chips directly to memory banks at a microscopic
level. Wow. Because they bypass electrical traces
entirely. They boast 10x lower latency. And they
claim an astonishing 25x greater bandwidth compared
to current industry approaches. If those specs
hold, it fundamentally changes how data centers
are built. It changes the entire physical architecture
of modern computing. We are moving from a wind
constrained by the friction of copper. to a world
operating at the speed of light. Let's step back
and look at the whole board here. The copper
wall is not just an academic theory or a distant
warning. No, it's not. It is a physical, hard
engineering constraint that slammed into the
AI industry the moment we tried to push 1 .6
terabits per second. Yeah, and the market reacted
with violent efficiency. Over $7 billion moved
in a matter of weeks. The biggest players in
the world, Nvidia, Marvell, Broadcom, are frantically
locking in their optical supply chains. TSMC
selling out their dedicated production lines
proves that this isn't a fad. Silicon photonics
is officially the new inevitable foundation of
all future AI infrastructure. Absolutely. For
you listening, try applying this three -layer
framework base, middle and top, to the next major
technological shift you encounter, whether it's
quantum computing or new battery chemistries.
It is a fantastic mental model for calibrating
risk. It cuts through the hype and truly helps
you understand who actually builds the complex
physical supply chains beneath the software.
And here is a final thought to chew on. The physical
limits of copper forced us to entirely rebuild
our infrastructure from the ground up. We literally
had to pivot to the physics of light just to
keep the AI boom alive. If you are wondering
why chat GPT or Claude might suddenly get 10
times faster and cheaper in a few years, it won't
be just a software update. No, it will be because
of microscopic glass. So what other invisible
physical limits of our current hardware are secretly
holding back the next massive leap in artificial
intelligence? Two sec silence. That's a great
question. Something to think about. Thanks for
taking this deep dive with us today. Keep learning,
keep questioning, and we'll catch you next time.
Out to your own music.