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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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$ORCL is early to one of the largest AI infrastructure buildouts in the world. If OCI keeps growing near these rates, cloud growth accelerates above 50% and customer prepayments reduce the funding burden then this selloff may eventually look like the painful funding phase before the harvest phase. Oracle now has to prove that massive AI demand can become massive shareholder value without too much dilution.

$ORCL is early to one of the largest AI infrastructure buildouts in the world. If OCI keeps growing near these rates, cloud growth accelerates above 50% and customer prepayments reduce the funding burden then this selloff may eventually look like the painful funding phase before the harvest phase. Oracle now has to prove that massive AI demand can become massive shareholder value without too much dilution.

Shay Boloor

69,765 Aufrufe • vor 2 Monaten

Today’s $IREN announcement of $2.8B in new multi-year AI Cloud contracts helps address the two biggest concerns surrounding its transformation into an AI cloud platform. The first is funding since building a GPU fleet requires billions of dollars before revenue arrives but customer prepayments covering ~45% of the related GPU spending reduce IREN’s upfront burden and demonstrate real financial commitment. The second is customer concentration since $MSFT and $NVDA provided strong validation but IREN still needed to prove it could attract a broader range of customers/workloads and these new contracts suggest that diversification is now underway.

Today’s $IREN announcement of $2.8B in new multi-year AI Cloud contracts helps address the two biggest concerns surrounding its transformation into an AI cloud platform. The first is funding since building a GPU fleet requires billions of dollars before revenue arrives but customer prepayments covering ~45% of the related GPU spending reduce IREN’s upfront burden and demonstrate real financial commitment. The second is customer concentration since $MSFT and $NVDA provided strong validation but IREN still needed to prove it could attract a broader range of customers/workloads and these new contracts suggest that diversification is now underway.

Shay Boloor

162,945 Aufrufe • vor 1 Monat

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

181,554 Aufrufe • vor 5 Monaten

🔥ED ZITRON: "IF OPENAI FAILS, ORACLE IS IN THE TOILET" Zitron called OpenAI "the Lehman Brothers of AI" and says its collapse would shake the entire market. Oracle's credit rating was downgraded to one level above junk specifically because of its $340 BILLION data center buildout for a company that may never be able to pay. "OpenAI IS the AI bubble. There is not another entity on Earth who can afford to pay for Stargate. No one."

🔥ED ZITRON: "IF OPENAI FAILS, ORACLE IS IN THE TOILET" Zitron called OpenAI "the Lehman Brothers of AI" and says its collapse would shake the entire market. Oracle's credit rating was downgraded to one level above junk specifically because of its $340 BILLION data center buildout for a company that may never be able to pay. "OpenAI IS the AI bubble. There is not another entity on Earth who can afford to pay for Stargate. No one."

Coin Bureau

50,922 Aufrufe • vor 1 Monat

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

134,760 Aufrufe • vor 2 Monaten

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 Aufrufe • vor 4 Monaten

$PLTR Rule of 40 score reached 155 and the metric has now expanded for 12 consecutive quarters as operating leverage continues improving with scale. That means Palantir is growing close to 100% while converting more than half of revenue into operating income which is a combination almost unheard of in large-scale software. $GOOGL, $AMZN, $MSFT and $META are spending hundreds of billions building the AI factories while Palantir sits above that infrastructure and turns the resulting intelligence into real-world outcomes without funding the physical buildout allowing far more incremental revenue to flow into profit and cash.

$PLTR Rule of 40 score reached 155 and the metric has now expanded for 12 consecutive quarters as operating leverage continues improving with scale. That means Palantir is growing close to 100% while converting more than half of revenue into operating income which is a combination almost unheard of in large-scale software. $GOOGL, $AMZN, $MSFT and $META are spending hundreds of billions building the AI factories while Palantir sits above that infrastructure and turns the resulting intelligence into real-world outcomes without funding the physical buildout allowing far more incremental revenue to flow into profit and cash.

Shay Boloor

401,670 Aufrufe • vor 20 Tagen

$GLW Corning: The AI Optical Infrastructure Springboard Strategy. Investment Thesis. New: 6/29/26. Corning has repositioned a traditional materials manufacturer into a critical supplier at the physical layer of AI infrastructure — a transition that leverages decades of fiber optics and photonics expertise into a market where that expertise is now mission-critical rather than commoditized. High-density fiber and advanced photonics are the connectivity backbone that AI data centers require as networking bottlenecks become increasingly binding constraints on cluster performance, and Corning's manufacturing scale and materials science depth position it as one of the few suppliers capable of meeting that demand at the volumes hyperscalers require. The NVIDIA and Meta partnerships are significant validation points. Both represent demanding customers whose technical requirements and qualification standards are rigorous, and their direct engagement with Corning signals that the company's optical infrastructure capabilities are viewed as strategically necessary rather than substitutable. That kind of direct hyperscaler relationship is difficult for competitors to displace once established, given the integration depth required in data center network architecture planning. The Springboard strategy is the financial framework converting the AI infrastructure opportunity into demonstrated margin improvement. Operating margin expansion that has already materialized provides credibility to the more aggressive 2030 revenue growth targets — this is not a purely forward-looking narrative but one with a track record of execution behind it. That said, the distance between current results and the 2030 targets is substantial, and the growth trajectory assumes continued AI infrastructure capital spending at a pace that has historically been difficult to sustain without periodic digestion phases. Capital intensity is the structural constraint on returns during the buildout phase. Scaling fiber and photonics manufacturing capacity to meet AI-driven demand requires sustained capital deployment, and the return on that investment depends on demand durability matching the capacity being built. Customer concentration compounds that risk — significant revenue exposure to a small number of hyperscaler relationships means that any shift in AI infrastructure capital spending plans at a major customer would disproportionately affect Corning's growth trajectory relative to a more diversified customer base. The Solar business is a complicating factor that sits somewhat apart from the core AI optical infrastructure narrative. Scaling that segment successfully requires different operational capabilities and serves a different demand driver, and management attention split across a capital-intensive solar scale-up alongside the AI infrastructure buildout introduces execution complexity that pure-play AI infrastructure companies don't carry. The valuation reflects multiple years of anticipated growth, which means the premium is justified only if execution stays on pace with the Springboard targets and AI infrastructure capital spending remains robust through the multi-year buildout period the thesis depends on. Corning's market position is genuinely dominant in its core optical infrastructure niche — the question is whether that dominance, expressed through a still-developing financial trajectory, supports a price that has already captured much of the anticipated upside.

$GLW Corning: The AI Optical Infrastructure Springboard Strategy. Investment Thesis. New: 6/29/26. Corning has repositioned a traditional materials manufacturer into a critical supplier at the physical layer of AI infrastructure — a transition that leverages decades of fiber optics and photonics expertise into a market where that expertise is now mission-critical rather than commoditized. High-density fiber and advanced photonics are the connectivity backbone that AI data centers require as networking bottlenecks become increasingly binding constraints on cluster performance, and Corning's manufacturing scale and materials science depth position it as one of the few suppliers capable of meeting that demand at the volumes hyperscalers require. The NVIDIA and Meta partnerships are significant validation points. Both represent demanding customers whose technical requirements and qualification standards are rigorous, and their direct engagement with Corning signals that the company's optical infrastructure capabilities are viewed as strategically necessary rather than substitutable. That kind of direct hyperscaler relationship is difficult for competitors to displace once established, given the integration depth required in data center network architecture planning. The Springboard strategy is the financial framework converting the AI infrastructure opportunity into demonstrated margin improvement. Operating margin expansion that has already materialized provides credibility to the more aggressive 2030 revenue growth targets — this is not a purely forward-looking narrative but one with a track record of execution behind it. That said, the distance between current results and the 2030 targets is substantial, and the growth trajectory assumes continued AI infrastructure capital spending at a pace that has historically been difficult to sustain without periodic digestion phases. Capital intensity is the structural constraint on returns during the buildout phase. Scaling fiber and photonics manufacturing capacity to meet AI-driven demand requires sustained capital deployment, and the return on that investment depends on demand durability matching the capacity being built. Customer concentration compounds that risk — significant revenue exposure to a small number of hyperscaler relationships means that any shift in AI infrastructure capital spending plans at a major customer would disproportionately affect Corning's growth trajectory relative to a more diversified customer base. The Solar business is a complicating factor that sits somewhat apart from the core AI optical infrastructure narrative. Scaling that segment successfully requires different operational capabilities and serves a different demand driver, and management attention split across a capital-intensive solar scale-up alongside the AI infrastructure buildout introduces execution complexity that pure-play AI infrastructure companies don't carry. The valuation reflects multiple years of anticipated growth, which means the premium is justified only if execution stays on pace with the Springboard targets and AI infrastructure capital spending remains robust through the multi-year buildout period the thesis depends on. Corning's market position is genuinely dominant in its core optical infrastructure niche — the question is whether that dominance, expressed through a still-developing financial trajectory, supports a price that has already captured much of the anticipated upside.

TheValueist

16,739 Aufrufe • vor 1 Monat

Is uranium the future of AI? As demand for cloud computing and AI models continues to explode, the real bottleneck is becoming power. That’s what led me to start looking at nuclear energy and uranium. Small modular reactors could become a major part of the solution, and if AI keeps demanding more electricity, the commodities that power that infrastructure could become just as important as the chips themselves.

Is uranium the future of AI? As demand for cloud computing and AI models continues to explode, the real bottleneck is becoming power. That’s what led me to start looking at nuclear energy and uranium. Small modular reactors could become a major part of the solution, and if AI keeps demanding more electricity, the commodities that power that infrastructure could become just as important as the chips themselves.

Kevin O'Leary aka Mr. Wonderful

34,028 Aufrufe • vor 4 Tagen

$GOOGL reports negative free cash flow for the first time in more than 20 years as AI spending surges. That spending is already translating into results with Cloud revenue reaching ~$25B, operating income more than tripling to ~$9B, margins expanding to 36% and backlog climbing to $514B. Alphabet is increasingly becoming a vertically integrated AI infrastructure company but it must fund the buildout before the cash flow arrives.

$GOOGL reports negative free cash flow for the first time in more than 20 years as AI spending surges. That spending is already translating into results with Cloud revenue reaching ~$25B, operating income more than tripling to ~$9B, margins expanding to 36% and backlog climbing to $514B. Alphabet is increasingly becoming a vertically integrated AI infrastructure company but it must fund the buildout before the cash flow arrives.

Shay Boloor

150,982 Aufrufe • vor 1 Monat

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

1,696,193 Aufrufe • vor 5 Monaten

$META is already using AI to improve its ad engine which makes it a clear winner in the AI economy. The market still wants proof that its massive infrastructure spend can create revenue beyond better ads which is why the compute business matters. If Meta monetizes just 20% of its data center capacity then it could generate $25B in profits and that optionality still doesn't look fully priced into the stock.

$META is already using AI to improve its ad engine which makes it a clear winner in the AI economy. The market still wants proof that its massive infrastructure spend can create revenue beyond better ads which is why the compute business matters. If Meta monetizes just 20% of its data center capacity then it could generate $25B in profits and that optionality still doesn't look fully priced into the stock.

Shay Boloor

85,425 Aufrufe • vor 1 Monat

“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

180,310 Aufrufe • vor 1 Jahr

OpenAI just got OFFICIALLY flagged as a company that might not be able to pay its bills. S&P Global Ratings just cut Oracle's long term credit rating from BBB to BBB-. One more cut and Oracle becomes a JUNK rated company for the first time in its history. But the reason S&P gave is what's really interesting here... They named OpenAI as a "key credit risk" inside the report. OpenAI is a private company. It carries no credit rating and has never been profitable. And a ratings agency just took the risk of that company failing and wrote it directly onto the credit file of a public company held inside pension funds and bond funds all over the world. OpenAI accounts for roughly HALF of Oracle's remaining performance obligations. That's the famous $638 billion backlog every bull points to as the reason to own the stock. Half of the asset is the risk. And then there's the maturity trap: Oracle's data center leases run 15 to 19 years. Its cloud customer contracts run about 5 years. Oracle disclosed both figures in its own annual report. So Oracle is signing 19 year obligations to serve 5 year promises made by a customer that has never earned a dollar of profit. If OpenAI cannot pay, Oracle gets left holding data center leases it may not be able to exit, and may have to re-lease to somebody else on worse terms. That is the entire downgrade in one sentence. The numbers underneath: Oracle spent roughly $55.7 billion on capital projects in fiscal 2026 and posted negative $23.7 billion in free cash flow. S&P now expects the fiscal 2027 cash flow deficit to widen to around negative $42 billion. That is nearly DOUBLE its previous estimate, and the agency admitted it had underestimated how much Oracle would need to spend. Oracle plans to raise up to $40 billion in fiscal 2027, including a potential $20 billion share sale that would add roughly 4.8% to its share count. They literally cannot borrow more without triggering the next downgrade, so shareholders are being diluted to protect the bondholders. And the funny part is that on the day of the downgrade, Oracle's stock went UP 2.65%. But on that same day, the spread on Oracle's BONDS widened. Equity investors looked at the $638 billion backlog and bought. Credit investors looked at the identical company and demanded to be paid more for the risk of holding it. Credit investors are the ones whose entire job is to price what goes wrong, so they just repriced Oracle. For context, Microsoft is rated AAA, Alphabet is AA+, and Amazon is AA. Oracle is chasing the same AI contracts from seven to nine notches further down the ladder. The day after the downgrade, the UK named Oracle, alongside three other cloud providers, a critical third party to the British financial system. Supervision by the Bank of England begins July 13. Oracle is the only one of those four sitting one notch above junk. Now follow the chain: OpenAI has never made a profit. OpenAI is half of Oracle's backlog. Oracle is one downgrade from junk. Oracle is now formally load bearing infrastructure for British banks. The business risk of an unprofitable private startup has traveled through a corporate balance sheet and landed inside the supervisory perimeter of a central bank. Nobody designed that. It happened one contract at a time. And the demand IS real. Oracle's cloud infrastructure revenue grew 93% last quarter. If this buildout works, it becomes one of the great corporate reinventions in history. But the whole structure now rests on one question that no rating agency, no bank and no regulator can answer: Can OpenAI pay its bills?

OpenAI just got OFFICIALLY flagged as a company that might not be able to pay its bills. S&P Global Ratings just cut Oracle's long term credit rating from BBB to BBB-. One more cut and Oracle becomes a JUNK rated company for the first time in its history. But the reason S&P gave is what's really interesting here... They named OpenAI as a "key credit risk" inside the report. OpenAI is a private company. It carries no credit rating and has never been profitable. And a ratings agency just took the risk of that company failing and wrote it directly onto the credit file of a public company held inside pension funds and bond funds all over the world. OpenAI accounts for roughly HALF of Oracle's remaining performance obligations. That's the famous $638 billion backlog every bull points to as the reason to own the stock. Half of the asset is the risk. And then there's the maturity trap: Oracle's data center leases run 15 to 19 years. Its cloud customer contracts run about 5 years. Oracle disclosed both figures in its own annual report. So Oracle is signing 19 year obligations to serve 5 year promises made by a customer that has never earned a dollar of profit. If OpenAI cannot pay, Oracle gets left holding data center leases it may not be able to exit, and may have to re-lease to somebody else on worse terms. That is the entire downgrade in one sentence. The numbers underneath: Oracle spent roughly $55.7 billion on capital projects in fiscal 2026 and posted negative $23.7 billion in free cash flow. S&P now expects the fiscal 2027 cash flow deficit to widen to around negative $42 billion. That is nearly DOUBLE its previous estimate, and the agency admitted it had underestimated how much Oracle would need to spend. Oracle plans to raise up to $40 billion in fiscal 2027, including a potential $20 billion share sale that would add roughly 4.8% to its share count. They literally cannot borrow more without triggering the next downgrade, so shareholders are being diluted to protect the bondholders. And the funny part is that on the day of the downgrade, Oracle's stock went UP 2.65%. But on that same day, the spread on Oracle's BONDS widened. Equity investors looked at the $638 billion backlog and bought. Credit investors looked at the identical company and demanded to be paid more for the risk of holding it. Credit investors are the ones whose entire job is to price what goes wrong, so they just repriced Oracle. For context, Microsoft is rated AAA, Alphabet is AA+, and Amazon is AA. Oracle is chasing the same AI contracts from seven to nine notches further down the ladder. The day after the downgrade, the UK named Oracle, alongside three other cloud providers, a critical third party to the British financial system. Supervision by the Bank of England begins July 13. Oracle is the only one of those four sitting one notch above junk. Now follow the chain: OpenAI has never made a profit. OpenAI is half of Oracle's backlog. Oracle is one downgrade from junk. Oracle is now formally load bearing infrastructure for British banks. The business risk of an unprofitable private startup has traveled through a corporate balance sheet and landed inside the supervisory perimeter of a central bank. Nobody designed that. It happened one contract at a time. And the demand IS real. Oracle's cloud infrastructure revenue grew 93% last quarter. If this buildout works, it becomes one of the great corporate reinventions in history. But the whole structure now rests on one question that no rating agency, no bank and no regulator can answer: Can OpenAI pay its bills?

Ricardo

303,068 Aufrufe • vor 1 Monat

$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 Aufrufe • vor 2 Monaten

$PLTR is one of the cleanest ways to play the AI cycle because it benefits from the entire infrastructure buildout without financing the data centers, chips, memory, power or networking underneath it. Palantir is also emerging as one of the biggest sovereign AI winners by building the control layer that determines what AI understands, which proprietary data it can access and what decisions or actions it can influence inside an organization. OpenAI and Anthropic create the intelligence while Palantir connects it to permissions, workflows and real operating systems where measurable economic value is produced.

$PLTR is one of the cleanest ways to play the AI cycle because it benefits from the entire infrastructure buildout without financing the data centers, chips, memory, power or networking underneath it. Palantir is also emerging as one of the biggest sovereign AI winners by building the control layer that determines what AI understands, which proprietary data it can access and what decisions or actions it can influence inside an organization. OpenAI and Anthropic create the intelligence while Palantir connects it to permissions, workflows and real operating systems where measurable economic value is produced.

Shay Boloor

200,100 Aufrufe • vor 19 Tagen

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

7,292,012 Aufrufe • vor 3 Monaten

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

120,848 Aufrufe • vor 5 Monaten

S&P just cut Oracle to one notch above junk, and the stock went UP anyway. Think about that for a second... Back in December I told you the AI arms race would keep rewarding capex right up until the moment it didn't, and I pointed straight at Oracle. The stock is now down more than 55% from its high and this week S&P downgraded its credit to the lowest rung of investment grade, which means one more cut and Oracle wears a junk rating for the first time in its history. The downgrade landed because the cash bleed is getting MUCH worse. S&P now sees Oracle burning close to $42 billion in free cash flow next year, nearly double its earlier estimate, with capex rocketing toward $90 billion and a single customer (OpenAI) sitting behind roughly half of that $638 billion backlog. The bond market looked at all of that and reached for insurance. The stock market looked at the exact same company and bid it higher. When those two disagree like this, 45 years in this business has taught me to side with the bondholders every single time. They get paid before shareholders do, so they tend to see the trouble first. And Oracle is now funding this buildout with equity instead of debt, with another $20 billion in stock issuance slated for this year. A company confident in its own cash flows borrows against them. A company bracing for a downgrade dilutes its shareholders instead. Oracle showed you which one it is. If you want to know how to actually make money in a market this dominated by Big Tech narratives, that is what July 22nd is for. 14 elite investors are sharing the specific longs and shorts they are backing with their own capital - for just $99. We entered the golden era of stock picking. Grab your ticket today:

S&P just cut Oracle to one notch above junk, and the stock went UP anyway. Think about that for a second... Back in December I told you the AI arms race would keep rewarding capex right up until the moment it didn't, and I pointed straight at Oracle. The stock is now down more than 55% from its high and this week S&P downgraded its credit to the lowest rung of investment grade, which means one more cut and Oracle wears a junk rating for the first time in its history. The downgrade landed because the cash bleed is getting MUCH worse. S&P now sees Oracle burning close to $42 billion in free cash flow next year, nearly double its earlier estimate, with capex rocketing toward $90 billion and a single customer (OpenAI) sitting behind roughly half of that $638 billion backlog. The bond market looked at all of that and reached for insurance. The stock market looked at the exact same company and bid it higher. When those two disagree like this, 45 years in this business has taught me to side with the bondholders every single time. They get paid before shareholders do, so they tend to see the trouble first. And Oracle is now funding this buildout with equity instead of debt, with another $20 billion in stock issuance slated for this year. A company confident in its own cash flows borrows against them. A company bracing for a downgrade dilutes its shareholders instead. Oracle showed you which one it is. If you want to know how to actually make money in a market this dominated by Big Tech narratives, that is what July 22nd is for. 14 elite investors are sharing the specific longs and shorts they are backing with their own capital - for just $99. We entered the golden era of stock picking. Grab your ticket today:

George Noble

18,966 Aufrufe • vor 1 Monat

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

1,098,185 Aufrufe • vor 5 Monaten