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$ORCL is borrowing aggressively to build AI data centers for a customer base heavily tied to OpenAI and the market is starting to question whether Oracle can fund that buildout without $MSFT, $GOOGL, $AMZN or $META level cash generation. The upside is that OCI now has one of the... show more

Shay Boloor

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Larry Ellison borrowed $125 billion to bet everything on a single customer that LOSES $5 billion a year. American banks are already refusing to lend him another dollar. And now that single customer has started to slowly walk away. This is one of the biggest gambles in tech history - and it’s NOT looking good: Oracle has $124.7 billion in debt on its books right now. That's more than the GDP of 100+ countries. Their free cash flow over the last 12 months? Negative $13.18 billion. They are spending more money than they make. And they're doing it on PURPOSE. Every other hyperscaler funds their AI buildout with cash. Google has cash. Amazon has cash. Microsoft has cash. Oracle has IOUs. They raised $58 billion in debt in just two months. $38 billion for Texas and Wisconsin data centers. $20 billion for New Mexico. And they need another $100 billion on top of that. Even US banks are starting to say no. TD Cowen reported that multiple banks have pulled back from Oracle lending. Borrowing costs have roughly DOUBLED since September. They're now paying interest rates typically reserved for companies rated below investment grade. Barclays downgraded their debt to underweight and warned Oracle could run out of cash by November 2026. So what does Larry Ellison do? He FIRES 30,000 people. Oracle is planning layoffs affecting up to 18% of its entire workforce. The goal is to free up $8 to $10 billion in cash flow just to keep the lights on while they build data centers for ONE customer: OpenAI. Oracle's $553 billion backlog sounds incredible until you realize a massive chunk of it flows through a single relationship. If OpenAI sneezes, Oracle catches pneumonia. And OpenAI is already sneezing... Sam Altman DROPPED plans to expand the Stargate site in Abilene, Texas. And the reason is insane: Nvidia's chips are improving so fast that by the time Oracle finishes building the data center, the processors inside it will already be outdated. Oracle is building with Blackwell chips. But Nvidia's new Vera Rubin platform delivers 5x the inference performance at 10x lower cost per token. So Oracle is borrowing billions to build facilities that will house yesterday's technology before they even open. The world of bits moves faster than the world of atoms. And Oracle is trapped in between. But here's where it gets wild: The earnings call revealed something most people missed... Oracle now REQUIRES certain customers to buy their own GPUs upfront and hand them over. They call it the "bring your own chips" model. Translation: Oracle can't afford the hardware anymore. So they're asking customers to fund the construction of Oracle's OWN data centers. The stock is still down 23% this year even after the 12% earnings pop. Moody's rates Oracle just two notches above junk status. Lower than Amazon, Alphabet, Meta, and Microsoft. And they have $248 billion in ADDITIONAL lease obligations that aren't even on the balance sheet yet. Larry Ellison is 81 years old and making the biggest bet in corporate history. He's trying to turn a legacy database company into a hyperscale AI cloud provider using other people's money. All while his only major customer is a startup that burns $5 billion a year and just had its expansion partner refuse to fund the next campus. The earnings beat was real. Revenue up 22%. Cloud infrastructure up 84%. But revenue growth funded by debt isn't growth. It's leverage. And leverage works both ways. If OpenAI stays loyal, if the Stargate buildout continues, if the debt markets keep lending, if Vera Rubin doesn't make their entire infrastructure obsolete overnight, then Larry Ellison pulled off the greatest corporate reinvention in history. But that's a lot of ifs for a company two notches above junk. Oracle is either the most undervalued AI play on the market or the most overleveraged house of cards since 2008. The next six months will tell us which one.

Larry Ellison borrowed $125 billion to bet everything on a single customer that LOSES $5 billion a year. American banks are already refusing to lend him another dollar. And now that single customer has started to slowly walk away. This is one of the biggest gambles in tech history - and it’s NOT looking good: Oracle has $124.7 billion in debt on its books right now. That's more than the GDP of 100+ countries. Their free cash flow over the last 12 months? Negative $13.18 billion. They are spending more money than they make. And they're doing it on PURPOSE. Every other hyperscaler funds their AI buildout with cash. Google has cash. Amazon has cash. Microsoft has cash. Oracle has IOUs. They raised $58 billion in debt in just two months. $38 billion for Texas and Wisconsin data centers. $20 billion for New Mexico. And they need another $100 billion on top of that. Even US banks are starting to say no. TD Cowen reported that multiple banks have pulled back from Oracle lending. Borrowing costs have roughly DOUBLED since September. They're now paying interest rates typically reserved for companies rated below investment grade. Barclays downgraded their debt to underweight and warned Oracle could run out of cash by November 2026. So what does Larry Ellison do? He FIRES 30,000 people. Oracle is planning layoffs affecting up to 18% of its entire workforce. The goal is to free up $8 to $10 billion in cash flow just to keep the lights on while they build data centers for ONE customer: OpenAI. Oracle's $553 billion backlog sounds incredible until you realize a massive chunk of it flows through a single relationship. If OpenAI sneezes, Oracle catches pneumonia. And OpenAI is already sneezing... Sam Altman DROPPED plans to expand the Stargate site in Abilene, Texas. And the reason is insane: Nvidia's chips are improving so fast that by the time Oracle finishes building the data center, the processors inside it will already be outdated. Oracle is building with Blackwell chips. But Nvidia's new Vera Rubin platform delivers 5x the inference performance at 10x lower cost per token. So Oracle is borrowing billions to build facilities that will house yesterday's technology before they even open. The world of bits moves faster than the world of atoms. And Oracle is trapped in between. But here's where it gets wild: The earnings call revealed something most people missed... Oracle now REQUIRES certain customers to buy their own GPUs upfront and hand them over. They call it the "bring your own chips" model. Translation: Oracle can't afford the hardware anymore. So they're asking customers to fund the construction of Oracle's OWN data centers. The stock is still down 23% this year even after the 12% earnings pop. Moody's rates Oracle just two notches above junk status. Lower than Amazon, Alphabet, Meta, and Microsoft. And they have $248 billion in ADDITIONAL lease obligations that aren't even on the balance sheet yet. Larry Ellison is 81 years old and making the biggest bet in corporate history. He's trying to turn a legacy database company into a hyperscale AI cloud provider using other people's money. All while his only major customer is a startup that burns $5 billion a year and just had its expansion partner refuse to fund the next campus. The earnings beat was real. Revenue up 22%. Cloud infrastructure up 84%. But revenue growth funded by debt isn't growth. It's leverage. And leverage works both ways. If OpenAI stays loyal, if the Stargate buildout continues, if the debt markets keep lending, if Vera Rubin doesn't make their entire infrastructure obsolete overnight, then Larry Ellison pulled off the greatest corporate reinvention in history. But that's a lot of ifs for a company two notches above junk. Oracle is either the most undervalued AI play on the market or the most overleveraged house of cards since 2008. The next six months will tell us which one.

Ricardo

181,176 views • 3 months ago

I think the $ORCL earnings has two truths at the same time. The first truth is that Oracle’s AI demand is real, massive and still accelerating but the second truth is that Oracle’s AI demand is expensive to deliver which meansthe stock now comes down to capex, financing, margins and dilution. The opportunity is massive because with ~$638B of backlog, Oracle now has the largest contracted backlog in tech and Larry Ellison is clearly betting the company’s future on OCI.

I think the $ORCL earnings has two truths at the same time. The first truth is that Oracle’s AI demand is real, massive and still accelerating but the second truth is that Oracle’s AI demand is expensive to deliver which meansthe stock now comes down to capex, financing, margins and dilution. The opportunity is massive because with ~$638B of backlog, Oracle now has the largest contracted backlog in tech and Larry Ellison is clearly betting the company’s future on OCI.

Shay Boloor

134,334 views • 21 days ago

What if the AI boom is not just a technology race, but a capital machine hiding in plain sight? The deeper I look at this ecosystem, the less it feels like a messy market and the more it looks like a closed financial loop. That is what makes this so striking. → Big Tech funds AI labs and infrastructure → AI labs and cloud players buy chips, GPUs, and networking → Model companies license capabilities back to the same giants funding the buildout What looks complicated is, in many ways, brutally simple. A money machine. And right now, that machine is being priced as if demand, revenue, and adoption will keep compounding with very little friction. That is the part I find most fascinating. Because the numbers are not just big. They are staggering. → Microsoft has invested more than $13B into OpenAI since 2019 → Oracle signed a $300B data centre capacity deal tied to OpenAI through 2029 → Meta is racing from roughly 150,000 NVIDIA GPUs in 2023 to around 1.3 million by the end of 2025 → Broadcom’s AI chip revenue is projected to jump from $3.8B in 2023 to $40B by 2026 What really stands out to me is how concentrated this loop has become. NVIDIA gets paid by nearly everyone. Infrastructure providers benefit early. AI companies are still betting on future monetization. Maybe it works. But that is the real question. Are we looking at durable economics, or one of the most elegantly circular bets the tech world has ever built? Do you think this AI capital loop is sustainable, or are we watching a beautifully engineered cycle that still has to prove itself? #AI #ArtificialIntelligence #OpenAI #NVIDIA #Microsoft #Infrastructure #DataCenters #Investing #BusinessStrategy #Innovation

What if the AI boom is not just a technology race, but a capital machine hiding in plain sight? The deeper I look at this ecosystem, the less it feels like a messy market and the more it looks like a closed financial loop. That is what makes this so striking. → Big Tech funds AI labs and infrastructure → AI labs and cloud players buy chips, GPUs, and networking → Model companies license capabilities back to the same giants funding the buildout What looks complicated is, in many ways, brutally simple. A money machine. And right now, that machine is being priced as if demand, revenue, and adoption will keep compounding with very little friction. That is the part I find most fascinating. Because the numbers are not just big. They are staggering. → Microsoft has invested more than $13B into OpenAI since 2019 → Oracle signed a $300B data centre capacity deal tied to OpenAI through 2029 → Meta is racing from roughly 150,000 NVIDIA GPUs in 2023 to around 1.3 million by the end of 2025 → Broadcom’s AI chip revenue is projected to jump from $3.8B in 2023 to $40B by 2026 What really stands out to me is how concentrated this loop has become. NVIDIA gets paid by nearly everyone. Infrastructure providers benefit early. AI companies are still betting on future monetization. Maybe it works. But that is the real question. Are we looking at durable economics, or one of the most elegantly circular bets the tech world has ever built? Do you think this AI capital loop is sustainable, or are we watching a beautifully engineered cycle that still has to prove itself? #AI #ArtificialIntelligence #OpenAI #NVIDIA #Microsoft #Infrastructure #DataCenters #Investing #BusinessStrategy #Innovation

Pascal Bornet

13,686 views • 2 months ago

Realizing that $GOOGL, $MSFT, $AMZN and $META all report earnings today and if they miss the market is literally going to zero.

Realizing that $GOOGL, $MSFT, $AMZN and $META all report earnings today and if they miss the market is literally going to zero.

Geiger Capital

296,044 views • 2 months ago

Oracle just told every AI company on earth the same thing. Your models are worthless. Not the technology, talent or the billions spent training them. But the data they were trained on. Larry Ellison, the man who built Oracle into the backbone of global enterprise just dropped a bombshell. He said ChatGPT, Gemini, Grok, and Llama, all of them are training on the exact same data. The entire public internet, every Wikipedia page, Reddit thread and every news article. That means they're all converging essentially becoming the same product with different logos. Ellison's word for it is commodities. But here's where it gets dangerous. He says the real gold isn't public data, It's private data. The medical records in hospital systems, the financial data in bank vaults. The supply chain secrets of every Fortune 500 and guess where most of that data already lives. Not Google, Amazon or Microsoft but inside Oracle. Oracle databases hold most of the world's high value private enterprise data. So Oracle just launched something called AI Database 26ai. It lets the top AI models, ChatGPT, Gemini, Grok, Llama reason directly over a company's private data, without that data ever leaving the vault. They're using a technique called RAG, Retrieval Augmented Generation. The AI doesn't train on your data, it searches it in real time. Think about what that means. A bank could ask AI to analyze every loan it's ever made without exposing a single customer record. A hospital could have AI diagnose patients using its full medical history without violating HIPAA. A defense contractor could let AI reason across classified operations without data leaving a secure environment. Ellison is betting this is bigger than the training market. Bigger than the GPU boom. Bigger than the data center buildout. He called it the largest and fastest growing market in history. The numbers back the ambition. Oracle's remaining performance obligations just hit $523 billion. That's contracted revenue not yet delivered and $300 billion of it comes from OpenAI alone. Cloud revenue hit $8 billion in a single quarter, OCI grew 66 percent and GPU revenue surged 177 percent. But here's the part nobody's talking about. If private data becomes the real AI moat, then whoever controls the database controls the future of AI. And that's a level of power that should make everyone uncomfortable.

Oracle just told every AI company on earth the same thing. Your models are worthless. Not the technology, talent or the billions spent training them. But the data they were trained on. Larry Ellison, the man who built Oracle into the backbone of global enterprise just dropped a bombshell. He said ChatGPT, Gemini, Grok, and Llama, all of them are training on the exact same data. The entire public internet, every Wikipedia page, Reddit thread and every news article. That means they're all converging essentially becoming the same product with different logos. Ellison's word for it is commodities. But here's where it gets dangerous. He says the real gold isn't public data, It's private data. The medical records in hospital systems, the financial data in bank vaults. The supply chain secrets of every Fortune 500 and guess where most of that data already lives. Not Google, Amazon or Microsoft but inside Oracle. Oracle databases hold most of the world's high value private enterprise data. So Oracle just launched something called AI Database 26ai. It lets the top AI models, ChatGPT, Gemini, Grok, Llama reason directly over a company's private data, without that data ever leaving the vault. They're using a technique called RAG, Retrieval Augmented Generation. The AI doesn't train on your data, it searches it in real time. Think about what that means. A bank could ask AI to analyze every loan it's ever made without exposing a single customer record. A hospital could have AI diagnose patients using its full medical history without violating HIPAA. A defense contractor could let AI reason across classified operations without data leaving a secure environment. Ellison is betting this is bigger than the training market. Bigger than the GPU boom. Bigger than the data center buildout. He called it the largest and fastest growing market in history. The numbers back the ambition. Oracle's remaining performance obligations just hit $523 billion. That's contracted revenue not yet delivered and $300 billion of it comes from OpenAI alone. Cloud revenue hit $8 billion in a single quarter, OCI grew 66 percent and GPU revenue surged 177 percent. But here's the part nobody's talking about. If private data becomes the real AI moat, then whoever controls the database controls the future of AI. And that's a level of power that should make everyone uncomfortable.

StockMarket.News

1,694,708 views • 4 months ago

“The Coatue team mapped out cloud revenue market share, Oracle at 5%, Amazon at 44% with AWS, Google 19%, Microsoft 30%. Next to that, they showed NVIDIA GPU allocation: Microsoft and Google match their cloud share. Amazon is 44% cloud revenue but only 20% GPUs. Oracle jumps from 5% to 19%. Cori comes out of nowhere at 11%.” “One obvious takeaway is that Amazon has half the share of GPUs than their share of AWS. So that could mean one of two things, either AWS is behind in AI, that could be one, or they're pursuing a different hardware strategy than its competitors.” — Bill Gurley Bill Gurley and Thomas Laffont Thomas Laffont

“The Coatue team mapped out cloud revenue market share, Oracle at 5%, Amazon at 44% with AWS, Google 19%, Microsoft 30%. Next to that, they showed NVIDIA GPU allocation: Microsoft and Google match their cloud share. Amazon is 44% cloud revenue but only 20% GPUs. Oracle jumps from 5% to 19%. Cori comes out of nowhere at 11%.” “One obvious takeaway is that Amazon has half the share of GPUs than their share of AWS. So that could mean one of two things, either AWS is behind in AI, that could be one, or they're pursuing a different hardware strategy than its competitors.” — Bill Gurley Bill Gurley and Thomas Laffont Thomas Laffont

bg2clips

180,260 views • 11 months ago

$IREN owns and develops large-scale, power-dense data center campuses in energy-rich regions for AI cloud, GPU clusters and build-to-suit data centers. Today’s 800MW Australia announcement reinforces the thesis that IREN can turn massive power capacity into AI infrastructure revenue faster than the market expected.

$IREN owns and develops large-scale, power-dense data center campuses in energy-rich regions for AI cloud, GPU clusters and build-to-suit data centers. Today’s 800MW Australia announcement reinforces the thesis that IREN can turn massive power capacity into AI infrastructure revenue faster than the market expected.

Shay Boloor

164,255 views • 28 days ago

Altimeter's Brad Gerstner and Gavin Baker argued that $SPCX SpaceX's AI compute business is scaling far faster than most investors expected. They believe the market is still underestimating the value of AI infrastructure, models, and orbital compute. Coming up right behind $AMZN AWS, $MSFT Azure, and $GOOGL Cloud?

Altimeter's Brad Gerstner and Gavin Baker argued that $SPCX SpaceX's AI compute business is scaling far faster than most investors expected. They believe the market is still underestimating the value of AI infrastructure, models, and orbital compute. Coming up right behind $AMZN AWS, $MSFT Azure, and $GOOGL Cloud?

Sam Badawi

16,157 views • 17 days ago

$AMZN at $250 is like $GOOGL at $200. • AWS grew 28% YoY in Q1 2026 — its fastest growth in 3+ years. • As AWS CEO Matt Garman said, AWS is growing faster in absolute dollars than $GOOGL Cloud and $MSFT Azure. • $AMZN owns 15% of Anthropic and 6% of OpenAI. The market is sleeping.

$AMZN at $250 is like $GOOGL at $200. • AWS grew 28% YoY in Q1 2026 — its fastest growth in 3+ years. • As AWS CEO Matt Garman said, AWS is growing faster in absolute dollars than $GOOGL Cloud and $MSFT Azure. • $AMZN owns 15% of Anthropic and 6% of OpenAI. The market is sleeping.

Daniel

29,050 views • 26 days ago

Jensen Huang, CEO of Nvidia, is telling you where to invest in 2026. He has personally directed Nvidia's capital into 8 specific companies for a combined total of over $45 BILLION. This is where the most important company in the AI economy is putting its money. Here’s the full list: OpenAI: $30 billion The largest commitment of the 8. Nvidia is funding the buildout of OpenAI's compute infrastructure from the inside. OpenAI is also Nvidia's single largest customer. GLW Corning: $3.2 billion Optical glass and fiber to physically connect AI clusters. You cannot move data between millions of GPUs without it. IREN: $2.1 billion AI cloud provider with one of the deepest power positions in North America. MRVL Marvell: $2 billion Custom networking chips that move data between GPUs at massive scale. LITE Lumentum: $2 billion Lasers and optical components for the fiber backbone of every AI data center. COHR Coherent: $2 billion Fiber optic transceivers that connect GPU clusters inside data centers. CRWV CoreWeave: $2 billion GPU-as-a-service provider. Nvidia's largest cloud customer outside the hyperscalers. NBIS Nebius: $2 billion AI cloud infrastructure company. Quietly building hyperscale GPU capacity for the AI labs. Whatever Nvidia is buying is where the money is going next. At The Assembly, we’re a team of 8 with one goal: help you find the right stocks early. Turn notifications on so you don’t miss our alerts. This is VERY important. If you’re not following us yet, you will regret it later.

Jensen Huang, CEO of Nvidia, is telling you where to invest in 2026. He has personally directed Nvidia's capital into 8 specific companies for a combined total of over $45 BILLION. This is where the most important company in the AI economy is putting its money. Here’s the full list: OpenAI: $30 billion The largest commitment of the 8. Nvidia is funding the buildout of OpenAI's compute infrastructure from the inside. OpenAI is also Nvidia's single largest customer. GLW Corning: $3.2 billion Optical glass and fiber to physically connect AI clusters. You cannot move data between millions of GPUs without it. IREN: $2.1 billion AI cloud provider with one of the deepest power positions in North America. MRVL Marvell: $2 billion Custom networking chips that move data between GPUs at massive scale. LITE Lumentum: $2 billion Lasers and optical components for the fiber backbone of every AI data center. COHR Coherent: $2 billion Fiber optic transceivers that connect GPU clusters inside data centers. CRWV CoreWeave: $2 billion GPU-as-a-service provider. Nvidia's largest cloud customer outside the hyperscalers. NBIS Nebius: $2 billion AI cloud infrastructure company. Quietly building hyperscale GPU capacity for the AI labs. Whatever Nvidia is buying is where the money is going next. At The Assembly, we’re a team of 8 with one goal: help you find the right stocks early. Turn notifications on so you don’t miss our alerts. This is VERY important. If you’re not following us yet, you will regret it later.

The Assembly

7,242,669 views • 1 month ago

$AMZN $GOOGL $MSFT and $META all understand that the risk of underinvesting in AI Capex is significantly larger than overspending. 👏🏻

$AMZN $GOOGL $MSFT and $META all understand that the risk of underinvesting in AI Capex is significantly larger than overspending. 👏🏻

Daniel Newman

12,455 views • 2 months ago

Kevin Warsh is already signaling what could be a major shift in Fed policy. While rising oil and a softer labor market have investors worried about inflation, he argues an AI-driven productivity boom from companies like $NVDA, $MSFT, $GOOGL and $AMZN could actually push prices lower. If that view gains traction, it could reshape how the market thinks about growth and rates. A productivity wave powered by AI could allow the economy to expand faster while inflation cools, changing the framework investors have used since the post-pandemic cycle.

Kevin Warsh is already signaling what could be a major shift in Fed policy. While rising oil and a softer labor market have investors worried about inflation, he argues an AI-driven productivity boom from companies like $NVDA, $MSFT, $GOOGL and $AMZN could actually push prices lower. If that view gains traction, it could reshape how the market thinks about growth and rates. A productivity wave powered by AI could allow the economy to expand faster while inflation cools, changing the framework investors have used since the post-pandemic cycle.

Sam Badawi

102,274 views • 3 months ago

I still own $IREN because I think the market is underestimating both the $NVDA alignment and how hard its power footprint is to replicate. If the company can turn ~5 GW of secured power into Nvidia-aligned AI cloud capacity then the market may start valuing the 10x gap between its power base and near-term AI cloud needs.

I still own $IREN because I think the market is underestimating both the $NVDA alignment and how hard its power footprint is to replicate. If the company can turn ~5 GW of secured power into Nvidia-aligned AI cloud capacity then the market may start valuing the 10x gap between its power base and near-term AI cloud needs.

Shay Boloor

1,306,711 views • 1 month ago

The neocloud category may be the most misunderstood corner of the AI trade because the market still treats these names as one uniform GPU-hours bet when they are actually very different business models: 1. $NBIS (Cloud Utility for the Agentic AI Age) $NVDA just chose Nebius as an architecture partner for the agentic AI era by co-designing AI factories with them, and the Rubin GPU access that comes with this partnership means Nebius gets the next-generation inference stack before almost anyone else in the market. At a $28B market cap, a 5GW power target and Nvidia’s engineering team embedded in the stack.. this is my favorite name in the neocloud category. 2. $IREN (Energy-to-Compute Engine of the AI Era) The dilution fear is real but the market is misreading it. IREN is not diluting to survive but diluting to scale into a $3.7B ARR target and the $9.3B in funding already secured through customer prepayments and GPU financing means the $6B ATM is optionality capital. The real bottleneck in AI infrastructure right now is power and IREN controls ~4.5GW of secured capacity while needing only ~500MW to support its ARR target by year-end. That 10x ratio of power capacity to near-term need is something no competitor can replicate quickly. 3. $CIFR (Landlord of the AI Utility Era) Cipher is not a pure neocloud but is a hyperscale infrastructure landlord signing decade-long leases to $AMZN AWS and $GOOGL while they fill the shells with compute. The AWS lease alone is expected to generate ~$700M in average annualized NOI for the next decade at nearly 100% NOI margins. Power-rich land is the scarcest resource in AI infrastructure and Cipher controls it with 600MW fully contracted, both facilities fully funded through non-recourse fixed-rate project debt and a 3.4GW development pipeline. 4. $CRWV (The Fragile Giant) CoreWeave’s demand backlog and revenue growth are very real but none of that matters if the capital markets close for even one quarter. Interest expense hit $388M in Q4 and management guided Q1 2026 interest expense to ~$550M which implies an annualized run rate above $2B before a single new data center comes online. The bull case requires capital markets to stay open, rates to cooperate, hyperscalers to honor take-or-pay contracts in full and construction to stay on time. That is a lot of dependencies in a macro environment where oil is approaching $100 and private credit is already showing signs of stress.

The neocloud category may be the most misunderstood corner of the AI trade because the market still treats these names as one uniform GPU-hours bet when they are actually very different business models: 1. $NBIS (Cloud Utility for the Agentic AI Age) $NVDA just chose Nebius as an architecture partner for the agentic AI era by co-designing AI factories with them, and the Rubin GPU access that comes with this partnership means Nebius gets the next-generation inference stack before almost anyone else in the market. At a $28B market cap, a 5GW power target and Nvidia’s engineering team embedded in the stack.. this is my favorite name in the neocloud category. 2. $IREN (Energy-to-Compute Engine of the AI Era) The dilution fear is real but the market is misreading it. IREN is not diluting to survive but diluting to scale into a $3.7B ARR target and the $9.3B in funding already secured through customer prepayments and GPU financing means the $6B ATM is optionality capital. The real bottleneck in AI infrastructure right now is power and IREN controls ~4.5GW of secured capacity while needing only ~500MW to support its ARR target by year-end. That 10x ratio of power capacity to near-term need is something no competitor can replicate quickly. 3. $CIFR (Landlord of the AI Utility Era) Cipher is not a pure neocloud but is a hyperscale infrastructure landlord signing decade-long leases to $AMZN AWS and $GOOGL while they fill the shells with compute. The AWS lease alone is expected to generate ~$700M in average annualized NOI for the next decade at nearly 100% NOI margins. Power-rich land is the scarcest resource in AI infrastructure and Cipher controls it with 600MW fully contracted, both facilities fully funded through non-recourse fixed-rate project debt and a 3.4GW development pipeline. 4. $CRWV (The Fragile Giant) CoreWeave’s demand backlog and revenue growth are very real but none of that matters if the capital markets close for even one quarter. Interest expense hit $388M in Q4 and management guided Q1 2026 interest expense to ~$550M which implies an annualized run rate above $2B before a single new data center comes online. The bull case requires capital markets to stay open, rates to cooperate, hyperscalers to honor take-or-pay contracts in full and construction to stay on time. That is a lot of dependencies in a macro environment where oil is approaching $100 and private credit is already showing signs of stress.

Shay Boloor

1,095,657 views • 3 months ago

Lagrange has joined the Oracle Partner Network to bring verifiable AI to defense, aerospace, and government systems. As a part of the network, we’re building DeepProve-powered use cases on Oracle Cloud Infrastructure (OCI) sovereign and mission-cloud solutions. Learn more: 🧵

Lagrange has joined the Oracle Partner Network to bring verifiable AI to defense, aerospace, and government systems. As a part of the network, we’re building DeepProve-powered use cases on Oracle Cloud Infrastructure (OCI) sovereign and mission-cloud solutions. Learn more: 🧵

LAGRANGE

518,321 views • 7 months ago

🚨 THIS IS HOW THE AI BUBBLE WILL BREAK THE S&P 500 Microsoft gave OpenAI $13B. OpenAI sent it back through Azure. Microsoft booked it as revenue. Google committed $40B to Anthropic. Anthropic agreed to send it back through Google Cloud and chips. They all call this loop “revenue.” Let's connect the dots: - Big Tech invests in the AI. - The AI buys Big Tech cloud. - Big Tech reports AI growth. - AI valuations explode. And Wall Street calls it demand. Ray Dalio warned that late-stage bubbles are driven by loops. That is what this looks like now. The technology is real. But the money is moving in circles. When holders finally ask how much of this “AI demand” is real, the bubble will burst. Reminder: I’ve called all the market tops and bottoms for the last 15 years, including the Bitcoin bottom at $16,000 and the top at $126,000. The next call will be even more important. When I exit the markets completely, I’ll post it here publicly like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.

🚨 THIS IS HOW THE AI BUBBLE WILL BREAK THE S&P 500 Microsoft gave OpenAI $13B. OpenAI sent it back through Azure. Microsoft booked it as revenue. Google committed $40B to Anthropic. Anthropic agreed to send it back through Google Cloud and chips. They all call this loop “revenue.” Let's connect the dots: - Big Tech invests in the AI. - The AI buys Big Tech cloud. - Big Tech reports AI growth. - AI valuations explode. And Wall Street calls it demand. Ray Dalio warned that late-stage bubbles are driven by loops. That is what this looks like now. The technology is real. But the money is moving in circles. When holders finally ask how much of this “AI demand” is real, the bubble will burst. Reminder: I’ve called all the market tops and bottoms for the last 15 years, including the Bitcoin bottom at $16,000 and the top at $126,000. The next call will be even more important. When I exit the markets completely, I’ll post it here publicly like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.

Alex Mason 👁△

285,034 views • 11 days ago

🚨JPMORGAN’S STEVE TUSA JUST DROPPED HIS 2026 OUTLOOK, IT’S BULLISH FOR DATA CENTERS🔥 Steve Tusa from JPMorgan has released his 2026 market predictions, with data centers sitting at the center of his outlook. Within the industrials space, he describes data centers as the primary driver, arguing that much of the group’s performance ultimately ties back to the AI and data center buildout. While he acknowledges some recent concern around the sustainability and length of the cycle, his on-the-ground read differs from the narrative that has taken hold in parts of the market. Demand tied to data centers has continued to accelerate through recent months, and he is clear that being materially underexposed to AI data centers is a mistake. In his view, pullbacks should be approached as opportunities rather than warnings. He directly addresses the overbuild debate, which remains a key source of skepticism. According to Tusa, there is no pause in real-world data center construction activity. Order activity has improved in recent weeks and is running stronger than it was around the end of the third quarter. Feedback from hyperscalers suggests supply is still struggling to catch up with demand, reinforcing his belief that the industry remains early in a multi-year buildout rather than late in the cycle. His comment about not seeing any “dark GPUs” sitting idle captures how tight the market still is. From a portfolio perspective, Tusa continues to favor staying with the AI data center buildout trade into 2026. Several data center-exposed industrial names have pulled back, but he views those moves as valuation resets driven by sentiment rather than a deterioration in underlying demand. That reset has created a more attractive entry point than what investors were facing just a few months ago. His preferred setup is a barbell approach. On one side are growth-oriented names with direct exposure to AI infrastructure demand. On the other are idiosyncratic margin expansion stories with some data center leverage, such as Johnson Controls, where he sees earnings growing in the mid-teens to around twenty percent over the next few years at reasonable valuations. Beyond that, he also points to select industrial names with cheaper economic leverage, but the primary focus remains on data center-driven growth and margin expansion. The broader takeaway is that despite skepticism and overbuild chatter, real-world demand, orders, and construction tied to data centers continue to strengthen. From JPMorgan’s perspective, this cycle still has meaningful runway left and is unlikely to be nearing its end anytime soon. $NBIS $IREN $NVDA $ORCL $AMD $GOOGL

🚨JPMORGAN’S STEVE TUSA JUST DROPPED HIS 2026 OUTLOOK, IT’S BULLISH FOR DATA CENTERS🔥 Steve Tusa from JPMorgan has released his 2026 market predictions, with data centers sitting at the center of his outlook. Within the industrials space, he describes data centers as the primary driver, arguing that much of the group’s performance ultimately ties back to the AI and data center buildout. While he acknowledges some recent concern around the sustainability and length of the cycle, his on-the-ground read differs from the narrative that has taken hold in parts of the market. Demand tied to data centers has continued to accelerate through recent months, and he is clear that being materially underexposed to AI data centers is a mistake. In his view, pullbacks should be approached as opportunities rather than warnings. He directly addresses the overbuild debate, which remains a key source of skepticism. According to Tusa, there is no pause in real-world data center construction activity. Order activity has improved in recent weeks and is running stronger than it was around the end of the third quarter. Feedback from hyperscalers suggests supply is still struggling to catch up with demand, reinforcing his belief that the industry remains early in a multi-year buildout rather than late in the cycle. His comment about not seeing any “dark GPUs” sitting idle captures how tight the market still is. From a portfolio perspective, Tusa continues to favor staying with the AI data center buildout trade into 2026. Several data center-exposed industrial names have pulled back, but he views those moves as valuation resets driven by sentiment rather than a deterioration in underlying demand. That reset has created a more attractive entry point than what investors were facing just a few months ago. His preferred setup is a barbell approach. On one side are growth-oriented names with direct exposure to AI infrastructure demand. On the other are idiosyncratic margin expansion stories with some data center leverage, such as Johnson Controls, where he sees earnings growing in the mid-teens to around twenty percent over the next few years at reasonable valuations. Beyond that, he also points to select industrial names with cheaper economic leverage, but the primary focus remains on data center-driven growth and margin expansion. The broader takeaway is that despite skepticism and overbuild chatter, real-world demand, orders, and construction tied to data centers continue to strengthen. From JPMorgan’s perspective, this cycle still has meaningful runway left and is unlikely to be nearing its end anytime soon. $NBIS $IREN $NVDA $ORCL $AMD $GOOGL

Jordan

56,476 views • 6 months ago

$NVDA CEO Jensen Huang said demand has gone parabolic because agentic AI has arrived, AI can now do productive work and tokens are becoming profitable. If tokens are profitable then model builders have a reason to produce more of them which means more inference, more compute and more demand across networking, memory, CPUs, power and data centers. The near-term stock reaction is about expectations but long-term story is still that the AI factory buildout is running through Nvidia which is why I think it has a real path to becoming the world’s first $10T company.

$NVDA CEO Jensen Huang said demand has gone parabolic because agentic AI has arrived, AI can now do productive work and tokens are becoming profitable. If tokens are profitable then model builders have a reason to produce more of them which means more inference, more compute and more demand across networking, memory, CPUs, power and data centers. The near-term stock reaction is about expectations but long-term story is still that the AI factory buildout is running through Nvidia which is why I think it has a real path to becoming the world’s first $10T company.

Shay Boloor

261,700 views • 1 month ago

Morgan Stanley recently reported that the amount of debt tied to AI is $1.2 trillion, with OpenAI at the center of the spend. But what's worth understanding is who is actually on the hook for the debt. It's not OpenAI, which has largely avoided tying the debt to its for- and non-profit entities, and as a result can aggressively expand without the burden of taking on high initial costs. Our discussion 👇

Morgan Stanley recently reported that the amount of debt tied to AI is $1.2 trillion, with OpenAI at the center of the spend. But what's worth understanding is who is actually on the hook for the debt. It's not OpenAI, which has largely avoided tying the debt to its for- and non-profit entities, and as a result can aggressively expand without the burden of taking on high initial costs. Our discussion 👇

TBPN

85,041 views • 8 months ago

Chris Camillo just made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.

Chris Camillo just made the most bullish case on $AMZN. Everyone worried when Amazon raised their capex to $200 billion Camillo believes they might make that $200 billion back on their Anthropic investment alone when Anthropic IPOs. What Amazon has done in the last 18 months is remarkable in scope. They didn't try to win the foundation model race against OpenAI and Google directly. They went a completely different direction, positioning themselves as the infrastructure underneath everything that is AI. Trainium chips, cloud buildout, advertising integration and equity stakes in two of the three most important AI companies on the planet. First Anthropic. Now $50 billion into OpenAI on top of that. And that OpenAI investment isn't just a financial bet. It ties OpenAI into Amazon's cloud ecosystem, probably permanently. Two of the big three AI labs now run on Amazon infrastructure. Google is the only one that doesn't. The market has spent two years debating who builds the best model. Amazon decided to own the plumbing those models run on and bought equity in the winners while they were at it.

Milk Road Macro

54,180 views • 1 month ago