🚨A single AI data center now draws 1 gigawatt.
These are the 10 companies building the infrastructure 🏗️
Global data center construction market: $2B+ annually.
Growing at AI speed. 💰
The 10 companies building the AI world:
1️⃣ DPR Construction 🇺🇸 mission-critical data centers
2️⃣ Turner Construction Company 🇺🇸 hyperscale infrastructure
3️⃣ AECOM 🇺🇸 advanced engineering and construction
4️⃣ Jacobs 🇺🇸 large-scale digital infrastructure
5️⃣ Fluor Corporation 🇺🇸 mission-critical facilities worldwide
6️⃣ Holder Construction 🇺🇸 complex hyperscale facilities
7️⃣ Fortis Construction 🇺🇸 high-performance data center builds
8️⃣ Skanska 🇸🇪 sustainable smart infrastructure
9️⃣ Arup 🇬🇧 energy-efficient resilient design
🔟 Mortenson 🇺🇸 next-generation data center projects
The problem they're all building around:
New grid interconnects take 5–7 years.
These facilities need power now.
So hyperscalers are bypassing the grid entirely signing private gas fired power deals directly at the data center site⚡
In my portfolio I already hold the company sitting on the gas.
I already hold the company sitting on the pipe.
These are the 10 companies building the infrastructure 🏗️
Global data center construction market: $2B+ annually.
Growing at AI speed. 💰
The 10 companies building the AI world:
1️⃣ DPR Construction 🇺🇸 mission-critical data centers
2️⃣ Turner Construction Company 🇺🇸 hyperscale infrastructure
3️⃣ AECOM 🇺🇸 advanced engineering and construction
4️⃣ Jacobs 🇺🇸 large-scale digital infrastructure
5️⃣ Fluor Corporation 🇺🇸 mission-critical facilities worldwide
6️⃣ Holder Construction 🇺🇸 complex hyperscale facilities
7️⃣ Fortis Construction 🇺🇸 high-performance data center builds
8️⃣ Skanska 🇸🇪 sustainable smart infrastructure
9️⃣ Arup 🇬🇧 energy-efficient resilient design
🔟 Mortenson 🇺🇸 next-generation data center projects
The problem they're all building around:
New grid interconnects take 5–7 years.
These facilities need power now.
So hyperscalers are bypassing the grid entirely signing private gas fired power deals directly at the data center site⚡
In my portfolio I already hold the company sitting on the gas.
I already hold the company sitting on the pipe.
✍1
🚨The NextEra-Dominion deal is completely remaking the North American power map.
This map from Orennia shows who controls electricity generation across North America state by state.
🇺🇸The US is a patchwork of regional utilities.
🇨🇦Canada is dominated by massive hydro monopolies.
But one combined entity NextEra-Dominion would become the largest power producer in 5 states simultaneously.
Including Virginia.
The data center capital of the world.
Here's the problem nobody is solving fast enough.
New grid interconnects take 5-7 years.
The queue is backed up for a decade.
Permitting, transmission buildout, state approvals the process was designed for a world that didn't need gigawatts delivered to a single campus in 18 months.
These facilities need power now.
So hyperscalers are bypassing the grid entirely.
They're signing private gas-fired power deals directly at the data center site⚡
Not waiting for the utility.
Not waiting for the interconnect queue.
Contracting directly with gas generators to build behind-the-meter capacity and commissioning it in months, not years.
The grid is too slow.
Private gas is the bridge.
In my portfolio, I already hold the company sitting on the gas.
I already hold the company sitting on the pipe.
But I just completed an analysis on the company that will benefit from this most and the upside is significant.
This map from Orennia shows who controls electricity generation across North America state by state.
🇺🇸The US is a patchwork of regional utilities.
🇨🇦Canada is dominated by massive hydro monopolies.
But one combined entity NextEra-Dominion would become the largest power producer in 5 states simultaneously.
Including Virginia.
The data center capital of the world.
Here's the problem nobody is solving fast enough.
New grid interconnects take 5-7 years.
The queue is backed up for a decade.
Permitting, transmission buildout, state approvals the process was designed for a world that didn't need gigawatts delivered to a single campus in 18 months.
These facilities need power now.
So hyperscalers are bypassing the grid entirely.
They're signing private gas-fired power deals directly at the data center site⚡
Not waiting for the utility.
Not waiting for the interconnect queue.
Contracting directly with gas generators to build behind-the-meter capacity and commissioning it in months, not years.
The grid is too slow.
Private gas is the bridge.
In my portfolio, I already hold the company sitting on the gas.
I already hold the company sitting on the pipe.
But I just completed an analysis on the company that will benefit from this most and the upside is significant.
✍1
Most people think AI runs on GPUs.
That's like saying the internet runs on browsers.
Modern AI is powered by an entire ecosystem of processors:
🧠 CPU → Coordinates everything
⚡ GPU → Trains massive models
🔷 TPU → Accelerates tensor operations
📱 NPU → Brings AI to phones & laptops
🚀 LPU → Delivers ultra-fast LLM responses
🌐 DPU → Handles networking, security & data movement
The interesting part?
Every AI breakthrough depends on ALL of them working together.
A trillion-parameter model is useless if:
• Data can't reach it fast enough
• Inference is too expensive
• Edge devices can't run it
• Infrastructure can't scale
The next AI race won't be won by the best model.
It'll be won by whoever builds the best compute stack.
Models get the headlines.
Chips run the world.
Which processor category do you think will see the biggest growth over the next 5 years?
That's like saying the internet runs on browsers.
Modern AI is powered by an entire ecosystem of processors:
🧠 CPU → Coordinates everything
⚡ GPU → Trains massive models
🔷 TPU → Accelerates tensor operations
📱 NPU → Brings AI to phones & laptops
🚀 LPU → Delivers ultra-fast LLM responses
🌐 DPU → Handles networking, security & data movement
The interesting part?
Every AI breakthrough depends on ALL of them working together.
A trillion-parameter model is useless if:
• Data can't reach it fast enough
• Inference is too expensive
• Edge devices can't run it
• Infrastructure can't scale
The next AI race won't be won by the best model.
It'll be won by whoever builds the best compute stack.
Models get the headlines.
Chips run the world.
Which processor category do you think will see the biggest growth over the next 5 years?
Compute continues to be the bottleneck.
Since my post 1 month ago...
$DGXX Digi Power X +103.54%
$HIVE Hive Digital +83.08%
$WYFI WhiteFiber +75.24%
$HUT Hut 8 +69.54%
$BTDR Bitdeer +52.22%
$RIOT Riot Platforms +51.23%
$NBIS Nebius +49.93%
$CLSK CleanSpark +46.72%
$ORCL Oracle +37.64%
$APLD Applied Digital +34.55%
$CORZ Core Scientific +35.31%
$CIFR Cipher Mining +34.21%
$IREN IREN +32.03%
Since my post 1 month ago...
$DGXX Digi Power X +103.54%
$HIVE Hive Digital +83.08%
$WYFI WhiteFiber +75.24%
$HUT Hut 8 +69.54%
$BTDR Bitdeer +52.22%
$RIOT Riot Platforms +51.23%
$NBIS Nebius +49.93%
$CLSK CleanSpark +46.72%
$ORCL Oracle +37.64%
$APLD Applied Digital +34.55%
$CORZ Core Scientific +35.31%
$CIFR Cipher Mining +34.21%
$IREN IREN +32.03%
🇦🇺☢️Australia holds roughly 30% of the world’s recoverable uranium resources.
That is a strategic advantage.
But policy still lags the geology.
Uranium is not on Australia’s federal critical minerals list.
Nuclear power is still banned at the federal level.
Several states have spent years restricting uranium mining, though some are now moving to unwind those barriers.
That is the contradiction:
Australia has one of the world’s largest uranium endowments.
But it still has not fully built a national strategy around it.
As nuclear demand rises, that gap becomes harder to ignore.
The rocks are strategic.
The policy is still catching up.
That is a strategic advantage.
But policy still lags the geology.
Uranium is not on Australia’s federal critical minerals list.
Nuclear power is still banned at the federal level.
Several states have spent years restricting uranium mining, though some are now moving to unwind those barriers.
That is the contradiction:
Australia has one of the world’s largest uranium endowments.
But it still has not fully built a national strategy around it.
As nuclear demand rises, that gap becomes harder to ignore.
The rocks are strategic.
The policy is still catching up.
A court just told GE Vernova: keep working on the project that owes you $360 million. 🧵
GE sent a termination notice after Vineyard Wind didn't pay $360 million.
Vineyard Wind sued.
A judge blocked the exit in April.
GE appealed, asked for reconsideration.
Both denied.
200+ GE employees legally compelled to stay on a project that hasn't paid them.
The judge's logic says everything: the only way to keep this $4.5 billion project alive is to force the supplier to stay.
If GE exits, financing collapses.
That's not a capital structure.... That's a project held together by injunction.
While offshore wind struggles under its own weight, a new model is being built quietly turbine by turbine, directly at the data center site.
Hyperscalers aren't waiting for the grid.
A mobile gas turbine is on site in 12-18 months.
A grid interconnect takes 5-7 years.
The binding constraint isn't gas.
It's turbines.
And 1 US-listed company owns that chokepoint.
GE sent a termination notice after Vineyard Wind didn't pay $360 million.
Vineyard Wind sued.
A judge blocked the exit in April.
GE appealed, asked for reconsideration.
Both denied.
200+ GE employees legally compelled to stay on a project that hasn't paid them.
The judge's logic says everything: the only way to keep this $4.5 billion project alive is to force the supplier to stay.
If GE exits, financing collapses.
That's not a capital structure.... That's a project held together by injunction.
While offshore wind struggles under its own weight, a new model is being built quietly turbine by turbine, directly at the data center site.
Hyperscalers aren't waiting for the grid.
A mobile gas turbine is on site in 12-18 months.
A grid interconnect takes 5-7 years.
The binding constraint isn't gas.
It's turbines.
And 1 US-listed company owns that chokepoint.
🇨🇭 Global One SI - Prompt
EUROPE WANTS TO TAX YOU ON MONEY YOU NEVER MADE. 🇪🇺 The Netherlands: 36% on unrealized gains from 2028. Your portfolio goes up on paper. You sell nothing. You receive no cash. The government sends a bill anyway. And the EU just proposed a 0.1% tax on every…
🚨If you live in Europe, paying for anything in cash above €10,000 becomes illegal from 10 July 2027, and anything over €3,000 will mean handing over your ID before the payment goes through.....
This is one EU law covering all 27 countries at once. Your government can set the limit lower than €10,000, but never higher, and several already have
France and Spain cap business cash payments at €1,000. Italy sits at €5,000. Greece at just €500. The rule only lets those numbers fall further over time, never rise
They say this is about catching criminals. But cash is still how most of Europe actually pays day to day. It's 63% of payments in Germany, 54% in Austria, 75% in Greece. Austria and Ireland have no cash limit at all today. From 2027 they will
The same year this limit lands, the European Central Bank begins a year-long test of the digital euro
A digital currency like this could come with limits on how much you hold, and digital money tried elsewhere has been built to expire or restrict how it gets spent
But cash, the one form of money that leaves no record and answers to nobody, may not stay open for much longer
This is one EU law covering all 27 countries at once. Your government can set the limit lower than €10,000, but never higher, and several already have
France and Spain cap business cash payments at €1,000. Italy sits at €5,000. Greece at just €500. The rule only lets those numbers fall further over time, never rise
They say this is about catching criminals. But cash is still how most of Europe actually pays day to day. It's 63% of payments in Germany, 54% in Austria, 75% in Greece. Austria and Ireland have no cash limit at all today. From 2027 they will
The same year this limit lands, the European Central Bank begins a year-long test of the digital euro
A digital currency like this could come with limits on how much you hold, and digital money tried elsewhere has been built to expire or restrict how it gets spent
But cash, the one form of money that leaves no record and answers to nobody, may not stay open for much longer
🚀 ASUS dropped the ProArt RTX Spark lineup at Computex 2026!
✦︎ ProArt P16 & P14 laptops + ProArt Mini PC
✦︎ Powered by NVIDIA RTX Spark superchip
→ 20-core Grace CPU + Blackwell GPU (6,144 CUDA cores)
→ Up to 128GB unified memory
→ 1 petaflop AI performance
✦︎ Super-small creator machines: 4K/3K Lumina Pro OLED displays, up to 99.9Wh battery, all-day runtime
✦︎ Built for: Local 120B LLMs, 90GB+ 3D scenes, 4K AI video generation, professional workflows
✦︎ ProArt Mini PC is a compact Local AI token factory with 10GbE + strong cooling 💪
Coming Fall 2026 🔥
✦︎ ProArt P16 & P14 laptops + ProArt Mini PC
✦︎ Powered by NVIDIA RTX Spark superchip
→ 20-core Grace CPU + Blackwell GPU (6,144 CUDA cores)
→ Up to 128GB unified memory
→ 1 petaflop AI performance
✦︎ Super-small creator machines: 4K/3K Lumina Pro OLED displays, up to 99.9Wh battery, all-day runtime
✦︎ Built for: Local 120B LLMs, 90GB+ 3D scenes, 4K AI video generation, professional workflows
✦︎ ProArt Mini PC is a compact Local AI token factory with 10GbE + strong cooling 💪
Coming Fall 2026 🔥
🇨🇭 Global One SI - Prompt
$HPE A few days ago I said: "AI isn't only about chips." Everyone talks about: $NVDA $MU $DELL But AI also needs: → networking → enterprise infrastructure → cloud architecture → data center modernization Today, HPE just delivered: - EPS: $0.79 vs $0.53…
The AI trade is evolving.
Phase 1:
$NVDA
Phase 2:
The companies helping enterprises actually deploy AI.
$HPE
$DELL
$SMCI
$MU
$IBM
Servers.
Networking.
Storage.
Memory.
Enterprise AI.
The AI buildout is becoming an ecosystem worth trillions.
And Wall Street is only beginning to understand how many winners there may be.
Phase 1:
$NVDA
Phase 2:
The companies helping enterprises actually deploy AI.
$HPE
$DELL
$SMCI
$MU
$IBM
Servers.
Networking.
Storage.
Memory.
Enterprise AI.
The AI buildout is becoming an ecosystem worth trillions.
And Wall Street is only beginning to understand how many winners there may be.
🔥1
🇨🇭 Global One SI - Prompt
The AI trade is evolving. Phase 1: $NVDA Phase 2: The companies helping enterprises actually deploy AI. $HPE $DELL $SMCI $MU $IBM Servers. Networking. Storage. Memory. Enterprise AI. The AI buildout is becoming an ecosystem worth trillions. And Wall…
$HPE may be becoming one of the most important AI infrastructure stories on Wall Street.
Everyone focuses on the chips.
But chips alone don’t build AI.
AI requires:
→ servers
→ networking
→ storage
→ data center infrastructure
→ enterprise deployment
And HPE is seeing demand explode.
The company just reported:
✓ Record revenue
✓ Record AI systems backlog
✓ Massive networking growth
✓ Strong cloud & AI demand
What stands out most isn’t the quarter.
It’s the backlog.
Backlogs tell you what customers are planning to buy next.
And right now customers are spending aggressively to build AI infrastructure.
The market may finally be realizing that AI isn’t a one-company story.
It is an entire ecosystem.
And $HPE is positioned right in the middle of it.
Everyone focuses on the chips.
But chips alone don’t build AI.
AI requires:
→ servers
→ networking
→ storage
→ data center infrastructure
→ enterprise deployment
And HPE is seeing demand explode.
The company just reported:
✓ Record revenue
✓ Record AI systems backlog
✓ Massive networking growth
✓ Strong cloud & AI demand
What stands out most isn’t the quarter.
It’s the backlog.
Backlogs tell you what customers are planning to buy next.
And right now customers are spending aggressively to build AI infrastructure.
The market may finally be realizing that AI isn’t a one-company story.
It is an entire ecosystem.
And $HPE is positioned right in the middle of it.
💯1
🇨🇭 Global One SI - Prompt
$FJET The breakout everyone ignored is starting to gain traction. A few days ago, the chart was quietly compressing beneath a major descending trendline. Today: - Trendline breakout confirmed - Volume expanding - Higher lows intact - Momentum accelerating…
$FJET Last few days, I talked about the technical setup.
Now, the story is becoming bigger.
The market is finally starting to pay attention to what Starfighters actually owns.
Most traders see:
A tiny micro-cap.
What they may be missing:
→ Space infrastructure exposure
→ Aerospace assets
→ Growing attention around commercial space
→ A valuation debate that is beginning to attract investors
The chart is already breaking out.
Volume is expanding.
And now the fundamental narrative is starting to catch up.
Sometimes the best moves happen when technicals and story align at the same time.
Now, the story is becoming bigger.
The market is finally starting to pay attention to what Starfighters actually owns.
Most traders see:
A tiny micro-cap.
What they may be missing:
→ Space infrastructure exposure
→ Aerospace assets
→ Growing attention around commercial space
→ A valuation debate that is beginning to attract investors
The chart is already breaking out.
Volume is expanding.
And now the fundamental narrative is starting to catch up.
Sometimes the best moves happen when technicals and story align at the same time.
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The CEO of NVIDIA, looked at Matt Murphy and said "The next trillion dollar company, ladies and gentlemen." (Save this).
NVIDIA already invested $2 billion in $MRVL Marvell in March 2026 as part of the NVLink Fusion partnership pulling Marvell's custom AI chip roadmap directly into the NVIDIA ecosystem and creating seamless integration between Marvell's hyperscaler ASICs and NVIDIA's GPUs, storage and networking infrastructure.
$NVDA NVIDIA does not invest $2 billion in a company and then call it the next trillion dollar company on a global stage unless it has deep knowledge of what is coming from inside that company's pipeline.
Understanding why Marvell is a trillion dollar company in the making requires understanding what Marvell actually is in 2026 which is very different from what most investors think.
Marvell is not primarily a networking chip company anymore but rather a full-stack hyperscaler AI infrastructure platform spanning custom AI accelerators, optical DSPs, photonic scale-up interconnects, Ethernet switching silicon, and storage controllers.
And every single one of those business lines is a direct pick-and-shovel play on the exact infrastructure that every hyperscaler on Earth is racing to build.
The custom ASIC business, Marvell's highest-growth and most strategically important segment is now anchored by three confirmed hyperscaler programs, Amazon Trainium (AWS's custom AI training and inference silicon), Microsoft Maia (Azure AI and OpenAI inference), and Google Axion (Google's custom CPU and adjacent AI programs).
Custom silicon revenue grew from essentially zero to $1.5 billion in FY2026, then accelerated sharply as volume production scaled.
Marvell now sees custom chip revenue topping $10 billion by fiscal 2029 meaning this single business line alone will represent roughly what the entire company earns today.
The optical DSP business is the second major leg.
Marvell is the dominant supplier of PAM4 and coherent optical DSPs, the chips that sit inside every 800G and 1.6T optical transceiver in every AI data center with over 3 billion ports shipped to date and a leadership position in 3.2T that is already in development.
The Celestial AI acquisition completed February 2026 for $3.25 billion added Photonic Fabric optical interconnect technology: a fundamentally new architecture for chip to chip and server to server optical connectivity that bypasses electrical interconnects entirely, operating at speeds and power efficiencies that copper cannot achieve at scale.
Marvell expects Celestial AI to begin contributing revenue in Q3 FY2028, and management called it the foundation of a brand-new semiconductor TAM meaning it is not competing for existing revenue pools, it is creating new ones.
The XConn acquisition also closed in February 2026 added PCIe 7.0 and CXL switching silicon, giving Marvell control over the memory expansion and pooling layer of next-generation AI server architecture.
Full-year FY2027 revenue is expected to approach $11.5 billion, 40% year-over-year growth with data center revenue growing 40% and optical interconnect growing 50%.
FY2028 targets approach $15 billion.
NVIDIA already invested $2 billion in $MRVL Marvell in March 2026 as part of the NVLink Fusion partnership pulling Marvell's custom AI chip roadmap directly into the NVIDIA ecosystem and creating seamless integration between Marvell's hyperscaler ASICs and NVIDIA's GPUs, storage and networking infrastructure.
$NVDA NVIDIA does not invest $2 billion in a company and then call it the next trillion dollar company on a global stage unless it has deep knowledge of what is coming from inside that company's pipeline.
Understanding why Marvell is a trillion dollar company in the making requires understanding what Marvell actually is in 2026 which is very different from what most investors think.
Marvell is not primarily a networking chip company anymore but rather a full-stack hyperscaler AI infrastructure platform spanning custom AI accelerators, optical DSPs, photonic scale-up interconnects, Ethernet switching silicon, and storage controllers.
And every single one of those business lines is a direct pick-and-shovel play on the exact infrastructure that every hyperscaler on Earth is racing to build.
The custom ASIC business, Marvell's highest-growth and most strategically important segment is now anchored by three confirmed hyperscaler programs, Amazon Trainium (AWS's custom AI training and inference silicon), Microsoft Maia (Azure AI and OpenAI inference), and Google Axion (Google's custom CPU and adjacent AI programs).
Custom silicon revenue grew from essentially zero to $1.5 billion in FY2026, then accelerated sharply as volume production scaled.
Marvell now sees custom chip revenue topping $10 billion by fiscal 2029 meaning this single business line alone will represent roughly what the entire company earns today.
The optical DSP business is the second major leg.
Marvell is the dominant supplier of PAM4 and coherent optical DSPs, the chips that sit inside every 800G and 1.6T optical transceiver in every AI data center with over 3 billion ports shipped to date and a leadership position in 3.2T that is already in development.
The Celestial AI acquisition completed February 2026 for $3.25 billion added Photonic Fabric optical interconnect technology: a fundamentally new architecture for chip to chip and server to server optical connectivity that bypasses electrical interconnects entirely, operating at speeds and power efficiencies that copper cannot achieve at scale.
Marvell expects Celestial AI to begin contributing revenue in Q3 FY2028, and management called it the foundation of a brand-new semiconductor TAM meaning it is not competing for existing revenue pools, it is creating new ones.
The XConn acquisition also closed in February 2026 added PCIe 7.0 and CXL switching silicon, giving Marvell control over the memory expansion and pooling layer of next-generation AI server architecture.
Full-year FY2027 revenue is expected to approach $11.5 billion, 40% year-over-year growth with data center revenue growing 40% and optical interconnect growing 50%.
FY2028 targets approach $15 billion.
✍1
🇨🇭 Global One SI - Prompt
$MRVL/USD H2 #Indicator #Signal #Trading #GlobalOneAI
JENSEN AT COMPUTEX TAIPEI JUST NOW:
- Marvell will become the next trillion-dollar company
- Marvell and Nvidia are strengthening their partnership to expand critical networking & connectivity to power AI data centers
Jensen touch... % 😂
- Marvell will become the next trillion-dollar company
- Marvell and Nvidia are strengthening their partnership to expand critical networking & connectivity to power AI data centers
Jensen touch... % 😂
💯1
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$NVDA CEO Jensen Huang revealed the Five Layer AI Model
These 5 layers include:
1) Chips - $AMD $AVGO $NVDA
2) Memory - $MU $SNDK $DRAM
3) Photonics - $AAOI $AXTI $AEHR
4) Compute - $CIFR $IREN $NBIS
5) Energy - $BE $FLNC $TE
These 5 layers include:
1) Chips - $AMD $AVGO $NVDA
2) Memory - $MU $SNDK $DRAM
3) Photonics - $AAOI $AXTI $AEHR
4) Compute - $CIFR $IREN $NBIS
5) Energy - $BE $FLNC $TE
✍1
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POV: It’s 2030 and $NOW stock price is at $500
You bought the $NOW dip at $85 in 2026
You bought the $NOW dip at $85 in 2026