u/Confident-Cell-2549

Trio-Tech International (TRT): A Deeply Mispriced Semiconductor Reliability Platform

Investment Thesis

Trio-Tech International is materially undervalued relative to its revenue base, operating history, and—critically—its increasing participation in the semiconductor burn-in and reliability ecosystem.

At approximately ~2.2–2.6× revenue, TRT continues to be valued as a low-growth, commoditized services provider. This characterization is increasingly inconsistent with the company’s actual trajectory. Recent developments indicate that TRT is operating within the same reliability bottleneck layer that has driven significant multiple expansion for peers such as Aehr Test Systems.

The market has already demonstrated a willingness to assign premium valuations to companies positioned in this segment. The question is no longer whether this layer deserves a premium multiple—it clearly does—but whether TRT is a legitimate participant. The evidence increasingly suggests that it is.
Established Operator with Structural Advantage

A defining characteristic of TRT is its decades-long presence in semiconductor testing and burn-in environments.

This is not a new entrant attempting to establish credibility. TRT has:
Operated across multiple semiconductor cycles
Built technical expertise in test and reliability processes. Maintained longstanding customer relationships

In contrast to many newer companies whose valuations are based on anticipated capability, TRT’s advantage lies in proven execution over time. The company is not attempting to enter the burn-in market—it has effectively been adjacent to it and is now moving more directly into its highest-value applications.

This experience base should not be discounted. In reliability testing, execution and consistency matter as much as innovation.
Strategic Positioning: Convergence with AEHR’s Core Value Driver

The most important development is TRT’s increasing exposure to burn-in tied to advanced semiconductors, including AI-related applications.

Recent activity includes:
A multi-million dollar order for burn-in boards associated with next-generation AI GPUs
Continued expansion into automotive semiconductor reliability, a segment with high qualification barriers and long product lifecycles.

Utilization of internal systems and capabilities, indicating a move beyond purely service-based activity.

These developments place TRT within the same functional layer that underpins AEHR’s valuation:

Semiconductor reliability testing is a bottleneck that becomes more valuable as device complexity increases.

As AI workloads scale and power densities rise, burn-in is not optional—it is required. This structural shift is not company-specific; it is industry-wide. TRT is now demonstrably participating in it.

Valuation: The Case for Parity
The current valuation gap is extreme:
TRT: ~$128M market cap, ~$49M revenue → ~2.6× sales
AEHR: ~$3.2B market cap, ~$45M revenue → ~71× sales
This gap reflects a market assumption that TRT is fundamentally a different, lower-quality business. That assumption becomes increasingly difficult to justify as TRT continues to demonstrate exposure to the same reliability-driven demand drivers.

If TRT is recognized, as it should be, as operating within the same structural segment as AEHR, then parity in valuation multiples becomes a legitimate framework, not an aspirational one.

At AEHR’s approximate ~71× revenue multiple:
Implied TRT valuation: ~$3.5B
Versus current: ~$128M
This represents a potential ~27× re-rating from current levels.

Even if one assumes some discount for scale, margins, or narrative clarity, the magnitude of the dislocation remains substantial.

Why the Market Has Not Yet Closed the Gap
The primary reason for the disconnect is not lack of capability, but lack of recognition.
TRT’s historical business mix has obscured its evolution. TRT announced Expansion in this area already.

The market continues to classify TRT based on its legacy profile.

In effect, TRT is being valued based on what it was, while AEHR is being valued based on what it is expected to become.

Conclusion

TRT is a longstanding semiconductor test operator that is increasingly aligned with one of the most valuable segments of the industry: burn-in and reliability testing for advanced semiconductors.

The market has already assigned premium valuations to this segment through companies like AEHR. TRT’s participation in the same ecosystem is becoming clearer, yet its valuation remains anchored at levels consistent with a commoditized services business.

As TRT continues to demonstrate repeatable exposure to burn-in demand tied to AI and automotive applications, the argument for valuation parity strengthens materially.

The opportunity is not dependent on TRT becoming a different company. It is dependent on the market recognizing what it has already become.

The market clearly already understands that the AI bottleneck is no longer just compute. It is bandwidth, latency, power, packaging, and optical connectivity.

This is widely publicized, it’s no secret and no longer debated.

AI needs optics, this is an obvious fact.

So which companies can actually manufacture the silicon photonics platforms today, that are needed to make that transition scale.

Tower Semiconductor is there today and it’s expanding capacity even more…based on prepaid commitments.

NVIDIA made it clear this weekend, that it is pulling the optical roadmap forward. Optical interconnects and co-packaged optics that many expected closer to 2030 are now targeting 2028. A two year acceleration.

Tower’s own silicon photonics capacity roadmap previously named to be fully ramped by 2028…..

On Tower’s last earnings call, management said its 1.6T is the fastest-growing silicon photonics node in the industry and that Tower is “by far the majority supplier” of 1.6T silicon PICs.

*Then NVIDIA confirmed a partnership with Tower shortly after.

Tower announced 1.6T data-center optical modules designed for NVIDIA networking protocols. *NVIDIA’s Gilad Shainer said NVIDIA is collaborating with Tower to advance next-generation silicon photonics for more efficient AI infrastructure.

On the earnings call, Tower’s CEO was asked whether the company’s 5x silicon photonics capacity expansion includes incremental demand from NVIDIA and partners.

His answer was yes.

He also explicitly said that: Tower increased its SiPho/SiGe CapEx plan to $920 million. The goal is more than 5x the Q4 2025 SiPho wafer shipment capacity by Q4 2026. Over 70% of total silicon photonics capacity is already reserved or in the process of being reserved through 2028, backed by customer prepayments. A prepayment arrangement customers requested, not one Tower proposed… think about that…

Towers ramp lines up perfectly with NVIDIA’s accelerated optical roadmap.

Meanwhile…..GlobalFoundries is trying to build its way into silicon photonics through acquisition and platform expansion. That validates the market, but it also shows how hard this stack is to assemble and how far away GFS is from being able to produce at scale.. it’s far behind and it’s still using external lasers and no where near heterogeneous on chip for 1.6t…

Intel has historical silicon photonics technology, but that is not the same thing as being publicly tied to NVIDIA’s current 1.6T AI optical ramp. Intels tech is hybrid and at this point legacy tech…

Tower’s PH18/PH18DA platform is not ordinary silicon photonics. It is bleeding-edge SiPho built for the next AI bandwidth node: 1.6T today, 3.2T next, heterogeneous III-V-on-silicon integration, InP-on-silicon, laser-integrated PICs, 400G-per-lane, LPO, and CPO.

Tower has shipped at scale high-yielding, high-quality SiPho wafers.

It is already the majority supplier of 1.6T silicon PICs.

It has deep ecosystem validation from Coherent, OpenLight/NewPhotonics, Anello, Salience, AVA, LightIC, and others across AI optics, optical switching, navigation, LiDAR, modulators, and next-generation PIC platforms. It’s the choice of quantum computing XNDU and multiple DOD awarded partners for the most advance tech...

-NVIDIA is accelerating optics.

-Tower already has scale and a public partnership with NVIDIA on 1.6T

-Tower already has announced its clear 1.6T leadership on its last earning call.

It no longer takes a deep understanding of Sipho to see the picture.

Wednesday I expect TSEM to beat and substantially raise guidance. Tower is one of the current bottleneck solutions that ready now…Wednesday I expect they will let the proverbial genie out of the bottle. -I am long TSEM

With Tower Semiconductor earnings coming up Wednesday, I thought it was worth recapping things and tying it together with what we have seen from companies that already reported across the AI infrastructure, optical, silicon photonics, and data-center stack.

Just the facts:

The recent earnings data across the stack has been extremely strong.

Lumentum reported record quarterly revenue of $808M, up 90% year over year, with operating margin expanding by 700 basis points sequentially. Even where revenue was basically around consensus, the important part was the forward signal: Q4 guidance was $960M to $1.01B, well above the prior quarter and pointing to continued AI optical demand acceleration.

Coherent reported $1.81B of revenue and $1.41 of non-GAAP EPS. Revenue came in slightly above estimates, and the company guided Q4 revenue to $1.91B to $2.05B, with non-GAAP EPS of $1.52 to $1.72. That is continued sequential growth in the same photonics/datacenter ecosystem Tower is tied to.

Arista beat clearly: $0.87 of non-GAAP EPS versus roughly $0.81 expected, a beat of about 7.4%, and $2.71B of revenue versus roughly $2.62B expected, a revenue beat of about 3.4%. Revenue was up 35.1% year over year. More importantly, management flagged supply constraints across wafers, silicon chips, CPUs, optics, memory and related components.

Fabrinet reported record revenue of $1.214B, up 39.3% year over year. Non-GAAP EPS was $3.72, beating estimates by about 3.9%. This is one of the cleanest optical manufacturing read-throughs in the stack.

VIAVI reported $406.8M of revenue, up 42.8% year over year. EPS came in at $0.27 versus roughly $0.24 expected, a beat of about 12.5%, and revenue beat by about 3.3%. That matters because VIAVI is tied into optical/network testing and datacenter demand.

Corning reported core sales of $4.35B, up 18% year over year, and core EPS of $0.70, up 30% year over year. Its Optical Communications segment grew 36%, and Corning disclosed two additional large, long-term hyperscale customer agreements.

AMD beat as well: $1.37 of adjusted EPS versus roughly $1.29 expected, a beat of about 6.2%, and $10.25B of revenue versus roughly $9.9B expected, a revenue beat of about 3.5%. Data Center revenue grew 57% year over year.

AEHR is a more nuanced read-through because revenue missed, but the production breadcrumb is extremely relevant: AEHR announced a silicon photonics customer for wafer-level burn-in tied to hyperscale datacenter optical interconnects. It also reported more than $37M of quarterly bookings and a book-to-bill over 3.5x, driven by AI and datacenter infrastructure demand.

So across the stack, the pattern is obvious:

Optics are strong. Stronger than what had been estimated and expected…

Demand is strong… that’s obvious from this week’s earnings reports and consistent guidance.

Supply constraints are showing up in wafers, chips, optics, memory, and networking hardware.

Companies exposed to the AI infrastructure bottleneck are beating numbers, guiding higher, or showing real production demand.

Now back to Tower… I’ve covered this before but it’s worth repeating…

Tower’s last Q&A may be one of the most underappreciated earnings-call exchanges I’ve seen.

Russell Ellwanger did not say, “we are going to beat.”

But he got about as close as a CEO reasonably gets.

He said:

“So the internal target should probably be more aggressive than the express target to the street, right?”

Then he followed it with:

“The demand is there, it’s committed, and it will be used. So the model will be hit.”

And then came the line I think the market is almost completely missing:

“Customers have committed to that demand to the extent we did not ask customers for reservation fees, they wanted it.”

That is not just committed demand.

That is prepaid demand.

And according to Tower, the customers asked for the reservation-fee structure.

That is a massive distinction.

This is not Tower chasing customers.

This is customers trying to lock down scarce Tower silicon photonics capacity.

Tower has already said over 70% of total SiPho capacity is reserved or in the process of being reserved through 2028, firmly backed by customer prepayment.

So when you combine the recent industry reports with Tower’s own Q&A, the setup into Wednesday becomes very hard to ignore.

Lumentum: 90% revenue growth and strong forward guidance.

Coherent: sequential growth guidance in photonics/datacenter.

Arista: EPS beat ~7.4%, revenue beat ~3.4%, and explicit optics/network supply constraints.

Fabrinet: record revenue, 39.3% growth, EPS beat ~3.9%.

VIAVI: EPS beat ~12.5%, revenue beat ~3.3%, revenue up 42.8%.

Corning: Optical Communications up 36%, with new long-term hyperscale agreements.

AMD: EPS beat ~6.2%, revenue beat ~3.5%, Data Center up 57%.

AEHR: silicon photonics production-test breadcrumb and AI/datacenter bookings over $37M.

And Tower: management said internal targets are more aggressive than what they are telling the Street, demand is committed, the model will be hit, and customers themselves wanted prepaid reservation fees.

That is the breadcrumb trail.

Actual reported results from companies tied to the same AI infrastructure, optics, testing, hyperscale, and datacenter supply chain.

$TSEM in my view is going to beat soundly and guide higher again…

The numbers across the stack are already pointing in the same direction.

$PPSI may be the last undiscovered AI power bottleneck gem hiding in plain sight

Everyone already found the obvious AI infrastructure trades.

$NVDA? Found.
$AVGO? Found.
$VRT? Found.
$ETN? Found.
$POWL? Found.
$MOD? Found.
Silicon photonics? The market is waking up fast.
CPO? Already getting priced.
Liquid cooling? Already crowded.
Transformers and switchgear? Already re-rated.

But the next bottleneck is not just chips.

It is time-to-power.

AI data centers do not just need electricity. They need deployable, onsite, megawatt-scale power now. The grid cannot keep up. Utility interconnection can take years. AI demand is moving faster than the electrical infrastructure buildout.

That is where Pioneer Power Solutions — $PPSI becomes wildly interesting.

This is still only about a $47M market-cap company today. Not $4.7B. Not $47B. About $47M.

And it is attacking one of the most urgent bottlenecks in the entire AI stack: mobile, modular, distributed power for edge AI, modular data centers, industrial compute, and power-constrained sites.

The key product is PRYMUS.

Pioneer says PRYMUS delivers scalable, pre-engineered power blocks from 1 MW to 10 MW and can be fully operational at a site in about six months, compared with the typical two-to-three-year timeline for utility-grade power. (Pioneer Power Solutions)

That is the whole thesis.

The market is obsessing over who gets the GPUs.

The better question is:

Who can power the GPUs before the grid shows up?

$PPSI might be one of the only tiny public companies positioned directly at that exact pain point.

And the valuation is insane compared with the opportunity.

Pioneer did $27.6M of 2025 revenue, up about 21% year over year. (Pioneer Power Solutions)

At roughly $47M market cap, the stock is trading around 1.7x trailing revenue. For a company with a credible shot at participating in the AI power bottleneck, that is almost absurd.

Now think about the upside.

If the market simply values $PPSI like a serious AI power infrastructure name, this does not need crazy math.

A move from $47M market cap to $150M is roughly a 3-bagger.

A move to $470M is roughly a 10-bagger.

A move to $1B would be roughly a 20-bagger.

And if PRYMUS becomes a recognized platform in the modular AI/data-center power market, a $1B valuation is not some fantasy number. The AI infrastructure market is throwing multi-billion-dollar valuations at companies solving power, cooling, interconnect, and deployment bottlenecks. PPSI is still sitting below $50M.

This is what asymmetry looks like.

One meaningful PRYMUS customer could change the story.
A few megawatt-scale deployments could change the revenue base.
A credible AI/modular data-center win could change the multiple.
A recognized role in “powering AI before the grid arrives” could completely re-rate the stock.

The beautiful part is that PPSI is not trying to invent quantum computing or sell some vaporware AI model.

It is solving a physical problem:

AI needs power.
Grid power is too slow.
PRYMUS is built for 1–10 MW rapid deployment.
The company is still worth less than $50M.

That is why this could be one of the last undiscovered gems in the AI infrastructure chain.

The first AI trade was chips.
The second was networking.
The third was silicon photonics.
The fourth was cooling and electrical gear.
The next one is deployable power.

And $PPSI is sitting right there before the crowd arrives.

Could this be a 3-bagger? Easily, if the market simply starts paying attention.

Could it be a 10-bagger? Yes, if PRYMUS gets real traction and PPSI becomes viewed as an AI power-gap company instead of a tiny EV/mobile-power name.

Could it be 1,000%+? Absolutely possible if the company lands major modular data-center or edge-AI power deployments.

Could it go 3,000%? That would mean a move toward roughly $1.4B market cap from today’s level. That is aggressive, but in an AI infrastructure mania, a company solving a real power bottleneck with megawatt-scale deployments does not need to be enormous to justify that kind of re-rating.

This is the kind of setup the market usually ignores until it is obvious.

By the time everyone agrees AI power is the next bottleneck, the easy money in the tiny names may already be gone.

$PPSI may be sitting at the exact intersection of:

AI power scarcity + modular data centers + edge compute + grid delays + mobile megawatt-scale deployment + nano-cap valuation.

That is the kind of asymmetry people claim they are looking for — until they actually see one before the market has blessed it.

$PPSI is not just an EV charging story anymore.

It may be an early public call option on the AI power bottleneck.

And if the market figures that out, this thing could re-rate violently.

Did Marvell already have the Tower path ready when it kicked POET to the curb?

I am not saying this is proven.

But I do think the breadcrumb trail is getting hard to ignore.

The official story is simple: Marvell canceled the POET/Celestial AI purchase orders because of alleged confidentiality violations. POET disclosed that Marvell claimed POET revealed purchase-order and shipping information in violation of confidentiality obligations.

Fine. That may be true.

But the bigger question is this:

Was the confidentiality issue just the clean contractual reason Marvell needed to walk away from an inherited Celestial AI supplier relationship and move toward a more scalable, foundry-backed silicon photonics ecosystem?

Because once you look at the timeline, Tower Semiconductor starts looking a lot more relevant than people want to admit.

Marvell did not cancel POET in a vacuum.

Marvell already had a relationship with Tower.

That is the key point.

Tower publicly identified Marvell in its silicon photonics / optical transceiver ecosystem, describing Marvell as a Tier 1 optical transceiver IC provider in a Tower investor presentation filed with the SEC. That means Tower is not some random speculative name being thrown into the discussion after the fact.

Marvell and Tower were already connected.

Now layer that on top of everything else.

Marvell bought Celestial AI because it wants to own a serious position in AI optical interconnects.

Marvell then announced a major NVIDIA partnership involving AI infrastructure and silicon photonics.

Marvell then acquired Polariton to strengthen its next-generation modulation roadmap.

Marvell then canceled POET’s inherited Celestial AI purchase orders.

Meanwhile, Tower is publicly tied to NVIDIA’s silicon photonics ecosystem and has been building one of the most visible open-foundry silicon photonics platforms in the market through PH18 and PH18DA.

That is the real setup.

This is not just “Marvell canceled POET.”

This is:

Marvell already had a Tower relationship.

Marvell bought Celestial AI.

Marvell partnered with NVIDIA on silicon photonics.

Tower is also publicly aligned with NVIDIA’s AI photonics ecosystem.

Marvell canceled POET’s inherited Celestial orders.

Marvell bought Polariton for next-gen optical modulation.

Tower’s PH18/PH18DA ecosystem includes OpenLight, Xscape Photonics, Lightwave Logic, and other companies building around scalable silicon photonics.

That is a very different story.

POET may have good technology. I am not saying POET is worthless or that its platform does not work.

But the issue in AI photonics is not just whether a technology works in a demo or early customer program.

The issue is whether it can scale.

Can it be manufactured reliably?

Can it be integrated into a broader ecosystem?

Can hyperscalers and Tier 1 chip companies trust the process?

Can the platform support multiple customers, multiple designs, and high-volume production?

Can it live inside the NVIDIA AI infrastructure stack?

That is where Tower becomes extremely interesting.

Tower’s PH18/PH18DA platform is not just a one-off proprietary device story. It is an open foundry silicon photonics ecosystem. OpenLight has announced volume production orders for 800G and 1.6T laser-integrated PICs on Tower’s platform. Xscape has worked with Tower on multi-wavelength laser sources for AI data-center fabrics. Lightwave Logic is integrating polymer modulators into Tower’s PH18 silicon photonics platform.

Those are not random science projects.

They are exactly the kinds of components and platform capabilities that matter for AI interconnects: lasers, modulators, PICs, optical engines, heterogeneous integration, and scalable manufacturing.

That is why the Marvell/Tower relationship matters so much.

If Marvell were starting from zero, the Tower theory would be weaker.

But Marvell was not starting from zero.

Marvell already had Tower in its orbit.

So the question becomes:

Did Marvell already have a more scalable Tower path available, making it much easier to cut POET loose after the confidentiality breach?

That is the question people should be asking.

Because Marvell is clearly not walking away from photonics. It is doing the opposite.

It bought Celestial AI.

It partnered with NVIDIA.

It bought Polariton.

It has its own silicon photonics light-engine roadmap.

It wants to be inside the future AI optical interconnect stack.

So when Marvell cancels POET, I do not read that as “Marvell no longer cares about photonics.”

I read it as potentially the opposite.

Marvell may be tightening control over its photonics roadmap.

And if you are Marvell, trying to serve NVIDIA-scale AI infrastructure, do you want to depend on a smaller proprietary supplier relationship inherited from Celestial?

Or do you want to lean into a scalable foundry-backed ecosystem where you already have a relationship, where NVIDIA is also involved, and where multiple photonics companies are already building around the same process platform?

That is why Tower looks so important.

Again, the missing piece is direct confirmation that Marvell moved the specific POET/Celestial function to Tower. I have not seen that publicly confirmed.

But the breadcrumb chain is strong:

Marvell and Tower already had a relationship.

Tower publicly named Marvell in its silicon photonics / optical transceiver ecosystem.

Marvell bought Celestial AI.

Marvell partnered with NVIDIA on AI infrastructure and silicon photonics.

Tower is publicly tied to NVIDIA’s silicon photonics ecosystem.

Marvell canceled POET’s inherited Celestial AI purchase orders.

Marvell acquired Polariton for next-generation optical modulation.

Tower’s PH18/PH18DA ecosystem includes OpenLight, Xscape, Lightwave Logic, and other photonics players targeting AI data-center interconnects.

OpenLight has announced volume production orders on Tower’s platform.

Xscape/Tower is targeting multi-wavelength laser sources for AI fabrics.

Lightwave/Tower is targeting high-speed modulators on PH18.

That is not proof.

But it is not nothing.

It suggests Marvell may have had a much better strategic alternative than continuing with POET.

The strongest version of the thesis is this:

Marvell did not simply cancel POET because of a random confidentiality dispute. The confidentiality issue may have given Marvell the clean legal reason to exit an inherited Celestial AI supplier relationship at the exact moment Marvell was consolidating a much larger NVIDIA-aligned silicon photonics strategy. Since Marvell already had a public relationship with Tower, and Tower is one of the most visible scalable open-foundry silicon photonics platforms tied to NVIDIA’s AI ecosystem, Tower becomes one of the most logical places to look for where Marvell could go next.

That does not mean POET’s technology failed.

It means Marvell may have decided the future belongs to scalable foundry-backed photonics platforms, not small supplier-dependent architectures.

And if that is the game, Tower is not a side character.

Tower may be one of the most important manufacturing platforms in the entire AI photonics stack.

$TRT … The Market Is Calling It Dilution. What We’re Seeing Is Fuel.

Everyone saw the $10M raise and stopped there.

That is the mistake.

Not all dilution is the same.

Bad dilution keeps the lights on.

Good dilution funds capacity, capability, and scale before a demand wave fully hits.

That is exactly what is happening here.

The AEHR playbook

Aehr Test Systems operates in burn in and reliability testing … the same critical bottleneck category as TRT.

Today AEHR has a market cap in the multi billion range off roughly tens of millions in revenue.

It is not being valued like a testing company.

It is being valued like AI infrastructure.

Why?

Because as AI scales … chips run hotter … failure becomes more expensive … validation becomes mission critical.

Burn in is not optional.

It scales with complexity.

Now look at Trio-Tech International

Roughly $49M in revenue … about a $60M market cap … around 1x sales.

Same category … same function … same tailwinds.

Completely different valuation.

Do the math

If TRT traded at AEHR type multiples …

$49M times 40 equals about $2.0B.

At 50x sales … closer to AEHR’s implied range … that is about $2.45B.

Today it sits around $60M.

That is a 30x plus gap.

Historical receipts … dilution that became fuel

This is not theory. This is exactly how multiple winners scaled.

NVIDIA

1999 IPO at $12 per share.

Issued millions of shares … raised about $48M.

That was dilution.

At the time … small company … unproven … needed capital to build.

Today … over a $5 trillion company.

That early dilution funded the platform.

Enphase Energy

2018 … stock around $2.

Raised about $20M by issuing millions of shares.

That was real dilution at a weak moment.

Used the capital to stabilize and scale.

Stock later ran over $300 at peak.

That was not survival dilution.

That was a turning point.

Axcelis Technologies

Traded in the low single digits years ago.

Invested through cycles … expanded capability.

Looked overlooked and small.

Stock later ran into the $100 plus range as semi demand surged.

That was capacity and positioning paying off.

AXT Inc

Raised capital to expand indium phosphide capacity … critical for photonics.

Market focused on dilution.

Reality … they were expanding into a supply constrained layer of the stack.

Same pattern.

Back to AEHR

Aehr Test Systems did not get a 40x plus multiple by accident.

They expanded capacity … captured a bottleneck … showed operating leverage.

Then the market repriced them as infrastructure.

What TRT is actually doing

This is where people are missing it.

TRT is not “trying” to scale into this.

They are scaling into it.

They are already seeing AI driven demand in testing.

They are already positioned in burn in and reliability.

They just raised capital to expand capacity ahead of that demand.

That is not theoretical.

That is happening.

What the market is missing

This is not random dilution.

This is capital raised ahead of demand … into a non optional bottleneck.

Burn in and reliability testing sit directly in the path of:

AI accelerators … silicon photonics … hyperscale deployments … automotive semiconductors.

As complexity rises … testing intensity rises.

No shortcuts.

This is how companies leapfrog

Weak companies dilute to survive.

Strong ones raise to scale.

TRT raised ahead of the curve.

That is how you move from an overlooked small cap to a critical layer in the stack.

Bottom line

The market sees dilution.

But if this capital expands capacity … increases throughput … and captures AI driven demand …

Then this is not dilution.

It is fuel.

And between AEHR today … and the historical paths of NVIDIA … Enphase … Axcelis …

There are more than enough receipts to understand what happens when the market finally catches up.

$TSEM … Foundries want to be them … the most advanced photonics companies want to be with them

Tower Semiconductor is the manufacturing layer behind the next generation of defense, aerospace, radar, photonics, sensing, navigation, space, and secure communications.

This is not emerging.

This is already happening.

The receipts are not subtle

Axiro Semiconductor (Radar / Defense):

“We selected Tower Semiconductor for their unparalleled SiGe technology expertise … fundamental to achieving the superior performance of our radar BFICs.”

That is definitive.

Axiro’s radar performance depends on Tower.

Then this:

“Working with Tower’s US facility enables us to reinforce our commitment to secure, mission-critical technology within the U.S. defense supply chain.”

That is not positioning.

That is dependence on trusted domestic manufacturing.

Northrop Grumman (Defense Prime Validation):

Tower was recognized with a Supplier Excellence Award supporting technologies tied to:

• national security

• advanced weapons

• aircraft

• missile defense

• space

Northrop does not hand out awards casually.

They award suppliers that are critical to mission execution.

ANELLO Photonics (Navigation / Photonics):

ANNELLO selected Tower for its silicon photonic waveguide platform enabling its optical gyroscope technology.

That platform supports:

• LiDAR

• sensing

• navigation

• optical communications

• microwave photonics

These are exactly the systems required in:

• GPS-denied environments

• drones

• robotics

• aerospace systems

DARPA (Next-Gen Photonics / Lasers):

DARPA selected Tower for the LUMOS program to bring:

• high-performance lasers

• optical amplifiers

… directly into domestic silicon photonics manufacturing.

Tower then confirmed integration of III-V lasers into its PH18 silicon photonics platform.

That is one of the hardest problems in photonics.

And it is being solved inside Tower’s manufacturing stack.

Put the stack together

Radar

Photonics

Navigation

Sensing

Space

Secure communications

Electronic warfare

All converging on one manufacturing layer.

Tower.

The conclusion is no longer debatable

It seems clear:

Tower is the manufacturing platform for the DoD photonics and advanced analog stack.

Tower is the trusted infrastructure that mission-critical aerospace and defense systems are being built on.

Why this matters more than people realize

Designing advanced systems is not the bottleneck.

Manufacturing them at scale, securely, and domestically is the bottleneck.

That is where Tower sits.

And that position is extremely hard to replicate.

The adoption pattern is repeating:

Military first

Aerospace and defense second

Commercial scale third

Radar

GPS

Satellites

The internet

Semiconductors

Now:

Photonics

Advanced sensing

AI infrastructure

Autonomous systems

The TAM is not just large … it is effectively unbounded

This is not one market.

This is a platform layer across multiple trillion-dollar verticals:

• Defense and aerospace

• AI infrastructure and data centers

• Silicon photonics and optical networking

• Autonomous systems and robotics

• Satellite and space systems (LEO and beyond)

• Advanced sensing and imaging

• RF, analog, and mixed signal electronics

Every one of these is expanding.

Every one is semiconductor intensive.

And almost all of them require:

• analog

• RF

• photonics

• imaging

• heterogeneous integration

That is Tower’s domain.

The lock-in is real

Once these systems are built on a process like Tower’s:

They do not move

They do not get requalified easily

They do not switch foundries

This is:

• long-duration revenue

• high switching costs

• mission-critical dependence

Final point

Axiro is not an outlier.

Northrop is not an outlier.

ANNELLO is not an outlier.

DARPA is not an outlier.

They are all pointing to the same reality…

#TSEM #TowerSemiconductor #SiliconPhotonics #Photonics #IntegratedPhotonics #OpticalInterconnect #OpticalNetworking #CoPackagedOptics #CPO #AIInfrastructure #DataCenter #Hyperscale #Semiconductors #Analog #RF #SiGe #MixedSignal #HeterogeneousIntegration

#NVIDIA #Broadcom #AVGO #Marvell #Coherent #Lumentum #AyarLabs #OpenLight #Cisco #Arista

#LightwaveLogic #LWLG #XscapePhotonics #XNDU #PolaritonTechnologies #AnelloPhotonics #ANELLO #RockleyPhotonics #POETTechnologies #CelestialAI #Lightmatter #PsiQuantum

#TSMC #STMicroelectronics #AnalogDevices #Skyworks #Qorvo

#DARPA #DoD #Aerospace #DefenseTech #TrustedFoundry #SecureSupplyChain #USManufacturing

#LEO #Satellites #SpaceTech #RFSystems #MillimeterWave #6G

#LiDAR #Navigation #SensorFusion #AutonomousSystems #Robotics #AdvancedSensing

#DeepTech #HardTech #NextGenTech #PhotonicsPlatform #AIRevolution #SemiconductorFoundry

The Silicon Photonics Stack and Where Tower Fits

1. What Nvidia Has Confirmed

NVIDIA has made several points clear:

Copper interconnects fail beyond ~2–2.5 meters at higher speeds

Next-generation AI systems (e.g., NVL1152) require rack-to-rack optical connectivity

The company is moving toward:

Silicon photonics

Co-packaged optics (CPO)

Nvidia is working with 20+ ecosystem partners to build this infrastructure

Conclusion: Optical interconnect is now required for scaling AI systems. This is not optional.

2. Tower’s Direct Positioning

Tower Semiconductor has publicly stated:

It is collaborating with Nvidia on 1.6T optical modules aligned with Nvidia networking protocols

CEO Russell Ellwanger stated that Tower is “by far the majority supplier of 1.6T silicon photonics PICs”

This places Tower directly in the 1.6T photonics ecosystem that Nvidia is scaling toward.

3. Who Tower Is Actually Shipping To

Tower typically does not ship directly to Nvidia. The supply chain is layered:

Step 1: Foundry (Tower)

Manufactures silicon photonics wafers (PICs)

Platforms include PH18 / PH18DA with laser integration capability

Step 2: Photonics Designers / Integrators

Companies such as OpenLight

Example: NewPhotonics has placed volume orders for 800G and 1.6T PICs built on the OpenLight/Tower platform

Step 3: Optical Module Manufacturers

Integrate:

PICs

Lasers

DSPs

Packaging

Produce full optical transceivers

Step 4: System Integration

Modules are used in:

Ethernet and InfiniBand switches

Future CPO-based systems

High-performance AI interconnect architectures

Step 5: End Deployment

Nvidia networking ecosystem

Hyperscale data centers

AI infrastructure buildouts

Key point: Tower supplies upstream components that feed multiple downstream vendors, not a single end customer.

4. Implication of “Majority Supplier” Claim

If Tower is the majority supplier of 1.6T PICs, then:

Multiple module vendors are sourcing from Tower

Those modules are being deployed into AI and hyperscale infrastructure

This reflects volume production, not early-stage R&D

This supports the view that 1.6T photonics is already in active deployment.

Bottom Line

Nvidia has confirmed that silicon photonics is required for future AI scaling

Tower is a confirmed participant in the 1.6T photonics ecosystem tied to Nvidia protocols

Tower likely supplies multiple photonics and module companies that feed into Nvidia systems and hyperscalers

Concise summary:

Nvidia is driving the demand for optical interconnect at scale. Tower is positioned upstream as a key supplier of the silicon photonics components that enable that transition.

Tower is “by far the majority supplier of 1.6T silicon photonics PICs”

Hey everyone! I'm u/Confident-Cell-2549, a founding moderator of r/Towersemiconductor.

This is our new home for all things related to Tower Semiconductor. We're excited to have you join us!

What to Post

Post anything that you think the community would find interesting, helpful, or inspiring. Feel free to share your thoughts, photos, or questions about.

Community Vibe

We're all about being friendly, constructive, and inclusive. Let's build a space where everyone feels comfortable sharing and connecting.

How to Get Started

1. Introduce yourself in the comments below.

2. Post something today! Even a simple question can spark a great conversation.

3. If you know someone who would love this community, invite them to join.

4. Interested in helping out? We're always looking for new moderators, so feel free to reach out to me to apply.

Thanks for being part of the very first wave. Together, let's make r/Towersemiconductor amazing.

This is a system level transition driven by physics:

electrical interconnects have hit power, heat, and bandwidth limits

the only scalable path forward is photonics + analog integration on chip

And that shift is not limited to data centers. It applies across sector:

optical interconnects and switching

LiDAR, robotics, and industrial sensing

LEO satellites and space communications

defense and aerospace systems

high-speed RF and real-world signal processing

This is the entire physical signal layer moving toward photonics.

What’s actually happening underneath

Across the stack you have independent technologies converging on the same manufacturing layer:

NLM Photonics — silicon-organic hybrid modulators validated on PH18

Lightwave Logic — electro-optic polymer modulators targeting foundry integration

Aeluma — quantum dot lasers on silicon

Xscape Photonics — optical switching fabric

Anello Photonics — optical gyros for navigation

Xanadu — photonic compute stack

Spark Photonics — design layer enabling cross-platform integration

Luceda / design ecosystem — enabling PDK-driven design adoption

NewPhotonics / module layer — tying into system-level deployment

Different materials, different architectures, different end markets.

Same requirement:

a scalable, heterogeneous, manufacturable process

And that process keeps pointing back to Tower Semiconductor.

Hard receipts (not theory)

Collaboration with NVIDIA on next-gen 1.6T optical infrastructure

Work with Coherent Corp. demonstrating 400G per lane toward 3.2T systems

Xscape Photonics building programmable multi-wavelength laser platforms on PH18

OFC ecosystem showing:

Luceda PDK integration

Alcyon IP libraries

DustPhotonics 800G / 1.6T modules

Salience optical switching

broader design + simulation toolchain support

Silicon photonics revenue scaling rapidly and already material

Management stating they are the majority supplier of 1.6T silicon PICs

Capacity + prepayment

Tower is expanding silicon photonics capacity by more than 5x.

And over 70% of that forward capacity is already reserved or in process of being reserved through 2028, supported by customer prepayments.

This is where I think people are completely misreading the situation.

Most investors are trained to think:

forward earnings are uncertain

demand may or may not show up

companies “build capacity and hope customers come”

That is not what is happening here.

This is the opposite.

This is:

customers writing checks today

to secure capacity years in advance

It’s effectively:

“If we pay you now, can you guarantee supply in 2–3 years?”

And management has been explicit:

they did not suggest prepayments

customers came to them

multiple customers

Why that matters

You do not prepay for capacity unless:

you believe the process works

you expect to stay on that process

you expect demand to exceed supply

This is not theoretical demand.

This is secured, forward demand behavior.

Forward valuation (this is where the disconnect is)

This is where I think the market is flat-out wrong.

Most people are valuing Tower on:

trailing earnings

legacy analog multiples

That misses what’s happening.

Let’s frame it properly.

Assumptions (conservative, not hype):

SiPho + RF + analog growth continues

capacity ramps over next 2–3 years

prepayments translate into utilization

If revenue scales meaningfully with this capacity build, you’re looking at:

Revenue expansion: significant multi-year growth

EBITDA expansion: operating leverage from high utilization

Illustrative forward view (not exact guidance, but directionally grounded):

EBITDA potentially moves toward ~$700M–$1B range over time

Current enterprise value implies a forward EV/EBITDA that could compress into the low-to-mid teens or below depending on ramp

That is not how hyper-growth infrastructure platforms are typically valued.

Compare that to peers / analogs in the space

Companies tied to similar themes:

Marvell Technology → trades at premium multiples driven by AI + interconnect growth

NVIDIA → extreme forward multiples due to infrastructure dominance

Photonics / optical component players (like Coherent Corp.) → trade higher on growth expectations

Even smaller, earlier-stage photonics companies often trade on:

revenue multiples

or speculative future TAM

Tower, by contrast:

has real revenue

has real customers

has pre-committed capacity

has a strong balance sheet

Yet is still often valued like a steady analog foundry, not a growth infrastructure platform.

CEO framing (this is important)

Management has already signaled the shift.

In late 2025 / December commentary, the CEO made it clear:

the company should now be viewed as a growth company

That lines up with:

revenue trajectory

capacity expansion

customer behavior

Why designs don’t move

Once designs are:

taped out

validated

tied into a PDK

They don’t just migrate.

Moving fabs means:

redesign

requalification

risk

So behavior shifts from experimentation to lock-in.

That’s how platforms form.

This is not a startup bet

The companies building on top:

may be early

may fail

But the manufacturing layer is not early and not unproven.

Tower has:

decades of analog + specialty process experience

real silicon photonics revenue

hyperscaler-driven demand

multi-year capacity commitments

strong cash position

Not limited to one vertical

This is not “AI optics.”

It is:

data centers

satellites

defense systems

robotics

sensing

optical switching

All of it converges on the same requirement:

high-speed, low-power, heterogeneous photonics + analog integration

Bottom line

This is not about picking a single photonics winner.

It is about identifying:

who becomes the manufacturing layer multiple winners depend on

Right now, the evidence shows:

independent technologies

independent companies

independent end markets

…all converging on the same platform.

That platform is Tower Semiconductor.

If this continues through:

PDK rollout

repeat tapeouts

capacity utilization

this will not be viewed as a niche semiconductor name.

It will be viewed as infrastructure.

And the key difference versus most stories is this:

This is not:

“build it and hope they come”

This is:

“they are already here, and they are paying in advance to make sure capacity exists when they need it”

Final thought on valuation

When:

forward earnings are partially de-risked by prepayments

demand is being pulled by hyperscalers

and capacity is being expanded against secured visibility

Then the appropriate framework is not:

trailing multiples

It is:

forward infrastructure growth multiples

And under that lens, Tower does not look expensive.

It is undervalued and in many areas first mover advantage, and a steadily increasing lead…

I’ve gone back through the last earnings call from Tower Semiconductor—especially the Q&A—and I honestly don’t understand how the market is still modeling this the way it is.

They didn’t come out and say “we’re going to beat,” but if you listen closely, they basically told you.

The Q&A Gave It Away

At one point, the CEO said:

“The internal target is probably more aggressive than what we’re expressing to the Street.”

Then he followed that with:

“Whether full qualification lands in November, December, January, or February, the demand is there, it’s committed, and it will be used.”

That’s not vague. That’s not cautious. That’s a company telling you demand is locked in and the only variable left is timing.

Silicon Photonics Isn’t Early Anymore

People still talk about this like it’s some future story.

It’s not.

SiPho revenue roughly doubled year over year

Q4 alone was running at a ~$350–$380M annualized pace

It’s becoming a meaningful part of total revenue

And it’s not just growth—it’s higher-margin growth.

The Prepaid Capacity Piece Matters More Than People Think

They’ve already said a large portion of their silicon photonics capacity is reserved or in the process of being reserved through 2028, backed by customer prepayments.

That’s not “we hope customers show up.”

That’s customers committing capital years in advance to lock in supply.

You don’t get that unless:

demand is real

supply is constrained

and what you’re building is critical

Japan Is the Part Everyone Is Misunderstanding

This is not a cold start.

The photonics processes are already qualified

They’re already shipping out of Fab 7

The expansion is about adding capacity to something that already works

Management even said that new tools can drive shipments relatively quickly once installed.

That only happens if customers are already lined up and qualified.

Put It Together

If you just connect what they actually said:

Demand is already committed

Internal targets are higher than what they’re guiding

Silicon photonics is already scaling

Capacity is being added to an already-qualified platform

A meaningful portion of that capacity is already spoken for

It’s hard to come to any conclusion other than this:

They’re set up to outperform what they told the Street.

Final Thought

They’re not going to come out and say it directly. That’s not how management teams operate.

But if you read the Q&A instead of just the headline numbers, it doesn’t sound like a company trying to figure things out.

It sounds like a company that knows exactly where it’s going—and is being conservative about how it communicates it.

Just my take, but this one feels pretty obvious if you’re actually paying attention.

The Real Advantage Tower Has Over GFS (That People Are Missing)

A lot of people don’t understand the nuances here and are lumping everything into “silicon photonics.”

Not everyone…..but enough that it’s distorting the conversation.

There are two very different architectures being treated as the same thing:

1. Monolithic silicon photonics

CMOS + RF + photonics on one chip

2. Heterogeneous on-chip laser integration

Integrating III-V laser material directly into the photonic chip

Those are not the same.

⸻

The Bottleneck Isn’t the Waveguide — It’s the Laser

Silicon can guide light.

Silicon can modulate light.

Silicon integrates well with electronics.

What it doesn’t do well is generate light.

That’s why the laser matters.

And that’s where the real split is happening.

⸻

Tower’s Advantage: Owning the Laser Layer

Tower’s ecosystem—through platforms like PH18/PH18DA and partnerships like OpenLight—is focused on heterogeneous integration, including on-chip laser capability.

That matters because it can:

* reduce coupling losses

* improve power efficiency

* simplify system design

* reduce packaging complexity

More importantly, it changes where the value sits:

Instead of the laser being an external dependency, it becomes part of the foundry platform.

That’s not incremental. That’s structural.

⸻

GFS: Different Approach

.

Their Fotonix platform is:

* CMOS + RF + photonics on one chip

* 300mm manufacturing

GFS still relies more on laser attach and packaging rather than clearly proven heterogeneous on-chip laser integration at scale.

That means:

* more interfaces

* more integration steps

* potentially higher system complexity

That makes it inferior in most cases.

.

⸻

The Lawsuit: Look Where the Fight Is

Now look at the lawsuit.

GFS is going after Tower over:

* legacy nodes

* RF

* power processes

Not advanced photonics.

That’s telling.

If the future battleground is AI interconnects, photonics, and co-packaged optics, why is the legal fight centered on older process technologies?

Because that’s where the current GFS revenue is, older tech…

This doesn’t look like a company asserting dominance in the next generation of tech.

It looks like a company protecting its existing position while the landscape shifts.

⸻

Why This Matters for AI

AI infrastructure is running into limits:

* copper doesn’t scale

* power consumption is exploding

* bandwidth is constrained

Photonics is the next step.

But the key question is simple:

Where does the laser live?

If it stays off-chip, systems remain more complex.

If it moves on-chip, integration tightens, efficiency improves, and the platform becomes more valuable.

If that shift happens at scale, the foundries that can support it capture more of the stack.

⸻

Bottom Line

This isn’t just GFS vs Tower.

It’s two different approaches to the same problem:

* GFS: broad, monolithic integration

* Tower: deeper, heterogeneous integration with a focus on the laser layer

And the lawsuit looks less like a forward-looking move and more like a competitive pressure tactic in legacy technology.

If you’re trying to understand where the real differentiation is emerging, this is one of the clearest places to look.

And right now, Tower has proven heterogeneous on chip and GFS has not…and GFS may never get there….

Right now…..New / next-gen designs are choosing Tower directly

* Nvidia (1.6T optics)

* OpenLight ecosystem

* NewPhotonics

* Xscape

* Scintil

These are architecture-level selections and the reasons..heterogeneous on chip….

Then there is XNDU …

* started with GFS-like path in 2022 ..never called

* 2026 XNDU has moved deep into Tower heterogeneous integration….

Everyone is chasing the same AI names right now.

NVIDIA, AMD, the obvious plays. Even testing names like AEHR have gotten attention.

But there’s a small company sitting in the background that almost nobody is talking about:

Trio-Tech International (TRT)

Here’s what caught my attention.

The market has already decided that semiconductor testing—especially burn-in and reliability—matters. AEHR is proof of that. It’s not a chip designer or a foundry, but it’s been rewarded because the role it plays is critical.

As chips get more complex, especially with AI and EV workloads, failure isn’t an option. That means more validation, more stress testing, more burn-in.

That trend isn’t going away.

Now look at TRT.

They’re already in that same part of the ecosystem:

•	Semiconductor testing

•	Burn-in

•	Reliability services

They’re not trying to be flashy, and they don’t have a clean, easy-to-sell story. It’s a smaller company with a mixed business model, which is probably why the market has mostly ignored it.

But the exposure is there.

To be clear, TRT is not AEHR.

AEHR is a focused, product-driven company with a strong narrative behind it. TRT is messier. Smaller. Less visible.

That’s exactly the point.

What I think is interesting is the gap between how the market values these kinds of businesses.

AEHR shows what investors are willing to pay for semiconductor testing exposure when it’s packaged the right way.

TRT shows what happens when that same exposure exists, but nobody is paying attention.

The bigger picture is simple.

AI chips are getting more powerful, hotter, and more complex. That increases the need for reliability testing across the board. It’s not optional. Every serious chip has to go through it.

So even if you don’t know which chip company wins long term, the need for testing keeps growing.

What makes TRT interesting as a setup is that it doesn’t need a huge transformation.

It doesn’t need to become AEHR.

It just needs the market to recognize that it operates in a part of the semiconductor stack that’s already been validated.

And because it’s small, even modest improvements in utilization or demand could flow through to earnings in a meaningful way.

There are real risks here.

It’s a microcap, so liquidity is limited. The business isn’t as clean or focused as investors usually prefer. And like anything tied to semiconductors, it’s still cyclical.

Also, there’s no guarantee the market ever pays attention.

But that’s usually where these kinds of opportunities come from.

The way I see it:

A microcap trading at a clear discount, with a re-rating coming once the market connects the dots.

Curious if anyone else has looked at this one or has a different take.