This layer captures emerging paradigm-shifting architectures: wafer-scale compute, photonic I/O, optical circuit switching, and physics-driven designs that break today’s limits.
Why it matters - These technologies change how entire AI systems are built and where the bottlenecks move.
Investor angle - High beta exposure to technologies that can reshape infrastructure.
Layer 8 - The Power Plant (Energy & Grid)
$GEV $VRT $FLNC $LEU
AI demand is colliding with grid constraints. Hyperscalers are turning to behind-the-meter power: gas turbines, microgrids, HV gear, SMRs, solar deployments, batteries, and nuclear-grade materials.
Why it matters - Compute follows power. Energy availability determines which regions can support AI growth.
Investor angle - Turbines, transformers, substations, storage, nuclear fuel, and grid upgrades enter a multi-year capex boom.
Layer 9 - The Sovereign Cloud (Infrastructure & Borders)
$MSFT $AMZN $GOOGL $NBIS $ORCL
Countries are building their own AI factories: sovereign regions, regulated clouds, local data centers, and national compute capacity.
Why it matters - AI is now a national-power asset. Sovereignty drives duplicated infrastructure and long-term demand.
Investor angle - Nations overbuild for control, increasing TAM far beyond pure efficiency models.
Layer 10 - The Digital Worker (Agentic Software)
$GOOG $MSFT $ADBE $CRM $PATH
AI shifts from tools to autonomous workers. Agents complete tasks, create output, and interact with workflows.
Pricing moves toward paying for outcomes rather than software seats.
Why it matters - This is the software layer where AI touches productivity and revenue directly.
Investor angle - Early but enormous potential to reshape enterprise economics.
Layer 11 - The Immune System (Security for Autonomous Systems)
$PANW $ZS $CRWD $OKTA
As agents proliferate, identity, permissions, and real-time trust become non-optional.
This layer protects autonomous systems from bad actors and bad outcomes.
Why it matters - AI expansion requires new security primitives built for machine decision-making.
Layer 12 - The Physical Body (Robotics & Automation)
$SYM $ROK $TSLA $TER $ISRG
AI leaves the data center and enters the physical world: humanoids, warehouse automation, manipulators, logistics robots, and real-world VLA stacks.
Why it matters - Robotics is a major link between AI and real GDP productivity.
Investor angle - A direct play on labor shortages, automation, and real-world deployment.
On this page I will be diving really deep into each layer
I'll lay the ground work for the importance of each layer
Where each one fits into the overall AI trade
And uncover the Alpha in the companies that investors care about (the cashtags posted are only a very small group of the companies that I will cover in each layer)
I'll post summaries on X and full deep dives on my free SS (l!nk in bio)
You will gain massive knowledge and insight and edge if you follow along this series
Highly recommend turning on your post notification as well!
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I’m tracking two key players in the photonics space, $ALMU and $POET, both building the future of high-speed connectivity.
Today, let's do a deep dive on Aeluma, a semiconductor company creating a platform that could redefine AI, autonomous driving, and quantum computing
You won't want to miss this thread 🧵
Cracking the Semiconductor Code $ALMU
For years, chip makers had a fundamental problem.
You could have incredible performance from exotic compound semiconductor materials, or you could have the massive scale and low cost of silicon manufacturing.
You couldn't have both.
Aeluma has cracked the code, developing a proprietary way to grow high-performance compound semiconductor materials directly onto large-diameter silicon wafers.
This platform gets the elite performance of specialized materials and the cost structure of mass-market production, a true holy grail for the industry.
This breakthrough means they can leverage the multi-trillion-dollar global silicon manufacturing infrastructure to build chips that were previously too expensive for anything but niche applications.
Product Deep Dive: Next-Gen SWIR Sensing $ALMU
Aeluma's first major product area is next-generation sensing.
The company is scaling Short-Wave Infrared (SWIR) sensors that are a massive leap over current tech.
SWIR light is much safer for the human eye, which allows systems to use more powerful illumination sources. This translates directly to longer range and better resolution for 3D sensing applications like advanced facial recognition or gesture control.
It also performs far better in bright sunlight, a critical advantage for outdoor systems like automotive LiDAR where solar interference can blind other sensors.
This superior performance in all conditions is exactly what the automotive and robotics industries have been waiting for.
Here is a list of 24 of my favorite names that I will be watching/buying during any down turn
I'll give a quick thesis on the investment and a chart with prices I'm watching
Let's dive in!
Disclaimer: None of this is financial advice or a recommendation. Do your own research
$SPY $QQQ $IWM
1/24 Innodata Inc. $INOD
Thesis: Innodata is a pure-play on the critical need for high-quality data in the Generative AI era. The performance and reliability of any Large Language Model are directly tied to the quality of the data it is trained on.
Innodata provides these essential data engineering services, positioning itself as a key partner for enterprises looking to build and deploy accurate, proprietary AI models. The company is a direct beneficiary of the massive, ongoing investment in the AI data pipeline.
Levels to Watch: The chart shows a stock that has just emerged from a year-long consolidation phase with a massive surge in both price and volume, indicating a significant change in character.
Buy Area: ~$70.60 (This represents the key breakout point from the prior trading range, which could now act as a new support shelf).
Support: ~$55.50 (The major resistance level from earlier in the year).
Resistance: ~$91.70 (The recent high).
2/24 Credo Technology Group $CRDO
Thesis: Credo is a key enabler play in the artificial intelligence and data center boom. The company provides the essential high-speed connectivity solutions such as chips, cables, and optical components that act as the nervous system for modern data infrastructure.
As hyperscalers and enterprises race to build out their AI capabilities, the demand for faster, more efficient data transfer explodes, placing Credo's technology at the heart of this secular growth trend.
Levels to Watch: The chart shows a stock in a powerful, long-term uptrend that is currently experiencing a healthy pullback.
Buy Area: ~$133.00 (This is a key area of interest where horizontal price support from early September converges with the primary ascending trendline that has been intact since May).
Support: ~$115.00 (Previous consolidation zone).
Resistance: ~$178.00 (The recent all-time high).
#CRDO #AIstocks
WhiteFiber $WYFI built one in months...
Out of a mattress factory.
That’s its edge: retrofits that are 2x faster and 40% cheaper.
Now it’s running a $90M GPU cloud and developing a 99MW NC site.
This thread unpacks the strategy, economics, comps, and risks 🧵
$CRWV $IREN $NBIS $WULF $SLNH
Strategy $WYFI
At its heart WhiteFiber runs a two-pronged strategy to capture value across the AI infrastructure stack.
First, its Colocation business acts as a specialized landlord, providing secure, power-dense facilities for customers like AI hardware firm Cerebras Systems to deploy their own servers.
Second, its higher-margin Cloud Services (GPUaaS) segment offers direct, on-demand access to high-performance computing on its own fleet of NVIDIA GPUs.
The linchpin is its "retrofit" model. Instead of building data centers from the ground up, $WYFI acquires and rapidly upgrades existing industrial sites.
Management claims this approach is "two times faster and 40% cheaper," a critical edge in a market where speed to deployment is paramount.
This strategy allows them to target buildout costs of $7-$9 million per megawatt, a significant potential saving over traditional greenfield projects.
Self-Funding Engine $WYFI
The power of the White Fiber model is its self-funding engine.
The colocation business provides a bedrock of financial stability through long-term, predictable contracts with creditworthy tenants, such as the anticipated seven-year term for the flagship NC-1 facility.
This recurring revenue stream is highly attractive to lenders, lowering the company's cost of capital and de-risking the overall enterprise.
This stable financial foundation then empowers the company to strategically channel capital, including its recent IPO proceeds, into the higher-growth, higher-return Cloud Services segment.
The company's own projections show a compelling ~30% unlevered IRR for its GPU cloud investments.
In essence, the steady, utility-like revenue from colocation funds the aggressive expansion of its GPU fleet, creating a virtuous cycle of growth without heavy reliance on dilutive financing.
Why can one company make $7 Million from a megawatt of power, while another makes just $2 Million?
It's the most important question for valuing AI infrastructure stocks like $WYFI, $IREN, and $RIOT. They are not the same business.
This thread breaks down the one metric that matters: revenue per MW. Here's how to tell the landlord from the manufacturer. 🧵
#WYFI #IREN #RIOT #AI #Investing #DataCenter
The Foundational Model - Pure-Play Mining $RIOT
Riot Platforms represents the large-scale, pure-play Bitcoin mining model.
Their business is a direct power-to-digital-asset conversion. They secure power infrastructure for the primary purpose of running their own mining fleet to earn Bitcoin.
Revenue Model: An industrial-scale digital asset production and energy arbitrage play.
Annual Revenue per MW: ~$1.5M - $2.5M.
This figure is directly calculable from the Bitcoin network's hash rate economics (hash price) and a company's reported power capacity and fleet efficiency.
The revenue is almost entirely dependent on the price of Bitcoin and their operational uptime.
#RIOT #Bitcoin #Mining #Energy
The Transitional Model - Infrastructure Arbitrage $IREN
Iris Energy is executing a strategic pivot. They are leveraging their core competency. Building and operating efficient, low-cost data centers to capture the higher-value AI market. This is a move up the value chain.
Revenue Model: An asset transition, capitalizing on existing infrastructure for a more lucrative purpose.
Annual Revenue per MW: A blended target of ~$3M - $5M.
AI colocation commands a significant market premium over crypto hosting due to more complex power, cooling, and security requirements.
This range reflects the higher lease rates for this specialized infrastructure, a fact supported by their public statements on seeking higher revenue per megawatt.
What if you could invest in the AI revolution but with a built-in safety net?
Smith-Midland $SMID is a key builder of vaults for AI data centers, but its less glamorous businesses, like making highway barriers, provide a powerful foundation.
This is a story high growth potential with a security blanket of diversification. 🧵
$NVDA $AMD $NBIS $CRWV
Think of $SMID as a three-legged stool.
Leg 1: AI Data Centers. They build the essential precast utility vaults that power the AI boom.
Leg 2: Public Infrastructure. They make the J-J Hooks barriers and Soundwalls lining America's highways.
Leg 3: Architectural. Their innovative SlenderWall panels are used on modern high-rises.
Each leg supports the company, providing a powerful and balanced business model.
The AI data center business is their high-growth engine.
In the AI gold rush, $SMID sells the "picks and shovels."
Their precast concrete vaults and buildings are critical for the rapid construction of new AI facilities, especially in their home turf of Virginia's "Data Center Alley."
This is their primary driver for explosive growth and where much of the upside lies.