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When does the AI spending actually end? It's the question Wall Street doesn't want to answer. The Big Four hyperscalers are pouring $600+ billion into AI infrastructure this year alone. That's triple what they spent two years ago. Amazon just guided $200 billion in 2026 capex. The company is... expected to go negative on free cash flow this year - somewhere between $17 billion and $28 billion in the red, depending on which bank you ask. Alphabet's free cash flow is projected to fall 90%. From $73 billion to $8 billion. These are the most profitable companies in history. And they're borrowing money to fund a buildout with no clear end date. The depreciation problem is what nobody wants to discuss: Nvidia chips run on a 2-3 year product cycle. Each new generation delivers 2-3x better performance. So the H100s shipping today will be economically obsolete by 2027. BUT the hyperscalers are depreciating these assets over 5-6 years. Meta extended its useful life estimates to five-and-a-half years. That single change cut $2.9 billion from their 2025 depreciation expense. Microsoft, Alphabet, Oracle - all made similar moves. Run the numbers and depreciation is understated by roughly $176 billion between 2026 and 2028. That means Oracle's earnings could be inflated by 27% and Meta's by 21%. This isn't fraud. GAAP allows it. But it's aggressive accounting that makes current earnings look far better than the underlying economics. The debt picture makes it even WORSE. The top five hyperscalers raised $108 billion in debt last year - more than 3x the prior nine-year average. JP Morgan projects $1.5 trillion in tech debt issuance ahead. They're even securitizing data center debt into asset-backed securities. $13.3 billion this year alone. Those structures have a history. This looks eerily similar to the data connectivity buildout circa 2000. In that cycle, telecoms built massive infrastructure on borrowed money chasing demand that never materialized. By 2002, less than 5% of capacity was in use. The pattern is familiar: Capex explodes. Returns don't materialize. Accounting flatters earnings. Debt bridges the gap. Then the music stops. I'm not making predictions about timing. But when free cash flow turns negative, when hyperscalers hold more debt than cash for the first time, when accounting changes are inflating earnings by double digits... The math changes. We've seen this play out before multiple times. AND IT DOESN'T END WELLshow more

George Noble

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37,099 次观看 • 7 个月前 •via X (Twitter)

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Big Tech is spending $700 BILLION on AI this year. But their cash flow is collapsing. Amazon is going into debt. Google's free cash flow is dropping 90%. And they're literally paying influencers $600,000 each to convince you AI is worth using. If this technology was as revolutionary as they claim, why are they spending half a million dollars per creator to sell it? Here's what's actually happening behind the scenes: This week, all four tech giants reported earnings at once and every single one dropped a spending number that made Wall Street lose its mind. Amazon: $200 billion in capex. The largest corporate capital expenditure in HISTORY. Stock dropped 9%. Google: $185 billion. Wall Street expected $120 billion. Stock dropped 5%. Meta: $135 billion. Double what they spent last year. Microsoft: down 17% this year, worst performer in the group. Combined 2026 AI infrastructure spend: almost $700 billion. But here's where it gets ugly. Amazon's free cash flow collapsed 71%. Morgan Stanley projects they'll burn through $17 billion in NEGATIVE free cash flow this year. Bank of America says the deficit could hit $28 billion. Amazon quietly filed with the SEC on Friday saying they might need to raise debt to keep building. Google's free cash flow is projected to crater 90%, from $73 billion down to $8.2 billion. They already did a $25 billion bond sale in November and their long-term debt QUADRUPLED last year. These companies are spending everything they have, then borrowing more, then spending that too. Now here's the part that got me thinking: CNBC just reported that Google, Microsoft, OpenAI, Anthropic, and Meta are paying influencers between $400,000 and $600,000 EACH to promote AI products on Instagram and YouTube. AI platforms spent over $1 BILLION on digital ads in 2025, a 126% jump year-over-year. Google and Microsoft's AI ad spending jumped 495% in January 2026 alone. Anthropic is running Super Bowl ads. OpenAI is flying creators to private events and covering all expenses. When was the last time a truly revolutionary technology needed a $1 billion ad campaign and $600K influencer deals to get adoption? Did the iPhone need influencer campaigns? Did Google Search need Super Bowl ads in 1998? Did email need a billion dollar marketing push? No. People just used them because the value was obvious. You know what DOES need massive paid promotions? Pharmaceutical drugs. Crypto exchanges. Online gambling apps. MLM companies. Products where adoption is driven by hype, not utility. And now, apparently, AI. So the pitch from Big Tech is: "This technology will eliminate your job. Also please use it. Here's $600K if you tell your followers it's cool." They need HUMANS to sell a product they designed to REPLACE humans. They need creators to promote a technology that will eventually make creators obsolete. They need influencers to build trust in a system that will eliminate the need for influencer marketing entirely. The question everyone should be asking: If $700 billion per year in spending can't produce a product that sells itself, when exactly does this start making money? Because right now the math is messed up. $700 billion in spending, cash flow crashing, stocks tanking, SEC filings about raising more capital, and the best growth strategy they've got is paying tiktokers to demo features. Either AI is about to deliver the greatest economic transformation in human history, or we're watching the most expensive corporate Hail Mary ever thrown. And the fact that they need to pay half a million dollars per influencer to convince you it's the first one isn't a good sign.

Big Tech is spending $700 BILLION on AI this year. But their cash flow is collapsing. Amazon is going into debt. Google's free cash flow is dropping 90%. And they're literally paying influencers $600,000 each to convince you AI is worth using. If this technology was as revolutionary as they claim, why are they spending half a million dollars per creator to sell it? Here's what's actually happening behind the scenes: This week, all four tech giants reported earnings at once and every single one dropped a spending number that made Wall Street lose its mind. Amazon: $200 billion in capex. The largest corporate capital expenditure in HISTORY. Stock dropped 9%. Google: $185 billion. Wall Street expected $120 billion. Stock dropped 5%. Meta: $135 billion. Double what they spent last year. Microsoft: down 17% this year, worst performer in the group. Combined 2026 AI infrastructure spend: almost $700 billion. But here's where it gets ugly. Amazon's free cash flow collapsed 71%. Morgan Stanley projects they'll burn through $17 billion in NEGATIVE free cash flow this year. Bank of America says the deficit could hit $28 billion. Amazon quietly filed with the SEC on Friday saying they might need to raise debt to keep building. Google's free cash flow is projected to crater 90%, from $73 billion down to $8.2 billion. They already did a $25 billion bond sale in November and their long-term debt QUADRUPLED last year. These companies are spending everything they have, then borrowing more, then spending that too. Now here's the part that got me thinking: CNBC just reported that Google, Microsoft, OpenAI, Anthropic, and Meta are paying influencers between $400,000 and $600,000 EACH to promote AI products on Instagram and YouTube. AI platforms spent over $1 BILLION on digital ads in 2025, a 126% jump year-over-year. Google and Microsoft's AI ad spending jumped 495% in January 2026 alone. Anthropic is running Super Bowl ads. OpenAI is flying creators to private events and covering all expenses. When was the last time a truly revolutionary technology needed a $1 billion ad campaign and $600K influencer deals to get adoption? Did the iPhone need influencer campaigns? Did Google Search need Super Bowl ads in 1998? Did email need a billion dollar marketing push? No. People just used them because the value was obvious. You know what DOES need massive paid promotions? Pharmaceutical drugs. Crypto exchanges. Online gambling apps. MLM companies. Products where adoption is driven by hype, not utility. And now, apparently, AI. So the pitch from Big Tech is: "This technology will eliminate your job. Also please use it. Here's $600K if you tell your followers it's cool." They need HUMANS to sell a product they designed to REPLACE humans. They need creators to promote a technology that will eventually make creators obsolete. They need influencers to build trust in a system that will eliminate the need for influencer marketing entirely. The question everyone should be asking: If $700 billion per year in spending can't produce a product that sells itself, when exactly does this start making money? Because right now the math is messed up. $700 billion in spending, cash flow crashing, stocks tanking, SEC filings about raising more capital, and the best growth strategy they've got is paying tiktokers to demo features. Either AI is about to deliver the greatest economic transformation in human history, or we're watching the most expensive corporate Hail Mary ever thrown. And the fact that they need to pay half a million dollars per influencer to convince you it's the first one isn't a good sign.

Ricardo

726,292 次观看 • 7 个月前

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 次观看 • 6 个月前

Wall Street is WRONG about Oracle. $ORCL is being pitched as the "fourth hyperscaler." The AI infrastructure play of a lifetime. 35 out of 46 analysts have a buy rating. Consensus price target is $246. The stock is at $172. Down 47% from its September high. Now let me explain what the bulls aren't telling you and why this will end HORRIBLY: Oracle's non-current debt has ballooned to $124.7 billion. Up from $85.3 billion a year ago. A 46% increase in 12 months. Total liabilities sit at $206 billion against shareholders' equity of $39 billion. That's a 5-to-1 leverage ratio on a company being pitched as a "safe" infrastructure play. But that $124.7 billion isn't even the full picture... Oracle has been using project financing structures (loans repaid from projected future cashflow) to keep tens of billions more in borrowing off its balance sheet entirely. So when analysts quote Oracle's debt load, they're UNDERSTATING the actual exposure by a meaningful margin. Interest expense jumped 32% YOY. Free cash flow is negative $24.7 billion on a trailing basis. The company is spending $48 billion a year in capex while generating roughly $17 billion in operating cash flow. They issued $43 billion in senior notes in 9 months. They are borrowing at a pace that would make a leveraged buyout firm nervous. And what did they get for all that spending? They fired 30,000 people. On March 31st, Oracle sent an email at 6 AM to tens of thousands of employees telling them their roles were eliminated. 18% of the global workforce gone in a single morning. TD Cowen estimates the layoffs save $8 to $10 billion in annual cash flow. Which tells you everything about the math: Oracle can't fund $50 billion in AI capex AND keep 162,000 people on payroll. So the people went. Net income was up 95% last quarter. The stock is still down 47% from its high. Mr. Market is telling you something. The earnings look great on paper partly because Oracle extended the useful life of its servers to 6 years, reducing depreciation expense by billions. I've been flagging this accounting game across the hyperscalers for months. It flatters the income statement while the balance sheet quietly deteriorates. Now let's talk about the $553 billion in Remaining Performance Obligations that every bull cites as the "reason" to own this stock: Roughly $300 billion of that is a SINGLE contract with OpenAI through the Stargate project. Revenue doesn't start flowing until 2027. And OpenAI itself expects to lose over $167 billion through 2028 even if it hits $100 billion in annual revenue. So Oracle is borrowing $125+ billion to build data centers for a customer that cannot even fund its own operations. And the data centers themselves are significantly behind schedule: The flagship Stargate campus in Abilene has been under construction since mid-2024. 2 years later, only 2 of 8 planned buildings are operational, covering about 200 megawatts of the planned 1.2 gigawatts. The remaining Stargate sites across Wisconsin, New Mexico, Michigan, and other locations are in the earliest stages of development. The total estimated cost to build out Oracle's 7 gigawatts of planned Stargate capacity runs around $340 billion. And lenders are already getting nervous. The Wall Street Journal reported that additional capacity at Abilene originally earmarked for OpenAI ended up going to Microsoft instead - because the banks financing the build were uncomfortable with their credit exposure to OpenAI as the ultimate customer. When your LENDERS don't trust your tenant's ability to pay, then there's SERIOUS issue. And by the time those data centers are fully built, the GPUs inside them will already be approaching obsolescence anyway. Nvidia releases new architectures annually. Each generation delivers dramatically more compute per watt. The hardware goes obsolete in 3 years but the debt used to buy it gets repaid over a much longer horizon. The AI infrastructure buildout is a treadmill, not a revolution. Oracle is the purest expression of that thesis. - $206 billion in reported liabilities. - Billions more hidden off-balance-sheet. - Negative $25 billion in free cash flow. - 30,000 people fired to fund the capex. - A single unprofitable customer behind over half the backlog. - Data centers years behind schedule. And 35 analysts saying buy. This doesn't sound right, does it?

Wall Street is WRONG about Oracle. $ORCL is being pitched as the "fourth hyperscaler." The AI infrastructure play of a lifetime. 35 out of 46 analysts have a buy rating. Consensus price target is $246. The stock is at $172. Down 47% from its September high. Now let me explain what the bulls aren't telling you and why this will end HORRIBLY: Oracle's non-current debt has ballooned to $124.7 billion. Up from $85.3 billion a year ago. A 46% increase in 12 months. Total liabilities sit at $206 billion against shareholders' equity of $39 billion. That's a 5-to-1 leverage ratio on a company being pitched as a "safe" infrastructure play. But that $124.7 billion isn't even the full picture... Oracle has been using project financing structures (loans repaid from projected future cashflow) to keep tens of billions more in borrowing off its balance sheet entirely. So when analysts quote Oracle's debt load, they're UNDERSTATING the actual exposure by a meaningful margin. Interest expense jumped 32% YOY. Free cash flow is negative $24.7 billion on a trailing basis. The company is spending $48 billion a year in capex while generating roughly $17 billion in operating cash flow. They issued $43 billion in senior notes in 9 months. They are borrowing at a pace that would make a leveraged buyout firm nervous. And what did they get for all that spending? They fired 30,000 people. On March 31st, Oracle sent an email at 6 AM to tens of thousands of employees telling them their roles were eliminated. 18% of the global workforce gone in a single morning. TD Cowen estimates the layoffs save $8 to $10 billion in annual cash flow. Which tells you everything about the math: Oracle can't fund $50 billion in AI capex AND keep 162,000 people on payroll. So the people went. Net income was up 95% last quarter. The stock is still down 47% from its high. Mr. Market is telling you something. The earnings look great on paper partly because Oracle extended the useful life of its servers to 6 years, reducing depreciation expense by billions. I've been flagging this accounting game across the hyperscalers for months. It flatters the income statement while the balance sheet quietly deteriorates. Now let's talk about the $553 billion in Remaining Performance Obligations that every bull cites as the "reason" to own this stock: Roughly $300 billion of that is a SINGLE contract with OpenAI through the Stargate project. Revenue doesn't start flowing until 2027. And OpenAI itself expects to lose over $167 billion through 2028 even if it hits $100 billion in annual revenue. So Oracle is borrowing $125+ billion to build data centers for a customer that cannot even fund its own operations. And the data centers themselves are significantly behind schedule: The flagship Stargate campus in Abilene has been under construction since mid-2024. 2 years later, only 2 of 8 planned buildings are operational, covering about 200 megawatts of the planned 1.2 gigawatts. The remaining Stargate sites across Wisconsin, New Mexico, Michigan, and other locations are in the earliest stages of development. The total estimated cost to build out Oracle's 7 gigawatts of planned Stargate capacity runs around $340 billion. And lenders are already getting nervous. The Wall Street Journal reported that additional capacity at Abilene originally earmarked for OpenAI ended up going to Microsoft instead - because the banks financing the build were uncomfortable with their credit exposure to OpenAI as the ultimate customer. When your LENDERS don't trust your tenant's ability to pay, then there's SERIOUS issue. And by the time those data centers are fully built, the GPUs inside them will already be approaching obsolescence anyway. Nvidia releases new architectures annually. Each generation delivers dramatically more compute per watt. The hardware goes obsolete in 3 years but the debt used to buy it gets repaid over a much longer horizon. The AI infrastructure buildout is a treadmill, not a revolution. Oracle is the purest expression of that thesis. - $206 billion in reported liabilities. - Billions more hidden off-balance-sheet. - Negative $25 billion in free cash flow. - 30,000 people fired to fund the capex. - A single unprofitable customer behind over half the backlog. - Data centers years behind schedule. And 35 analysts saying buy. This doesn't sound right, does it?

George Noble

58,284 次观看 • 4 个月前

Google just posted negative free cash flow for the first time since it went public in 2004. This is the company that was supposed to fund AI out of pocket change. One of the most profitable ad businesses ever built. YouTube, Android, a growing cloud arm. Instead capex doubled to almost 45 billion in a single quarter. Buybacks suspended. 20 billion in new debt, 85 billion in new equity, just this year. 2026 guidance already raised to 195 to 205 billion. JPMorgan thinks 2027 could hit 378 billion. For one company. The question was never just whether the AI payoff justifies the spending. It is what all that capital, power and construction capacity is pulling away from everywhere else.

Google just posted negative free cash flow for the first time since it went public in 2004. This is the company that was supposed to fund AI out of pocket change. One of the most profitable ad businesses ever built. YouTube, Android, a growing cloud arm. Instead capex doubled to almost 45 billion in a single quarter. Buybacks suspended. 20 billion in new debt, 85 billion in new equity, just this year. 2026 guidance already raised to 195 to 205 billion. JPMorgan thinks 2027 could hit 378 billion. For one company. The question was never just whether the AI payoff justifies the spending. It is what all that capital, power and construction capacity is pulling away from everywhere else.

Jeffrey P. Snider

25,237 次观看 • 1 个月前

Google just reported $99 billion in profits it never actually received. Alphabet posted net income of $112.1 billion for a single quarter. Earnings per share came in at $9.11 against a Wall Street estimate of $2.87. That is one of the largest profit quarters any company has ever printed. Yet the stock fell about 7% the same day. When people read past the headline and opened the earnings release, they found the reason sitting in one footnote... $99 billion of that profit came from a line called other income. Alphabet describes it as "primarily the result of net unrealized gains on our equity securities." So Google did not sell anything. It marked up shares it already owned and ran the increase through its income statement. That single line added $77.1 billion to net income after tax. It accounted for $6.26 of the $9.11 in earnings per share. Strip it out and adjusted earnings per share were $2.85. Analysts wanted $2.89. The ACTUAL business missed. Now here is what makes this insane: Most of that $99 billion came from two holdings, SpaceX and Anthropic. SpaceX went public on June 12 at roughly $1.77 trillion, up from about $400 billion a year earlier. Alphabet's stake is worth $94.1 billion, and roughly $80 billion of it sits under sale restrictions. Anthropic went from a $350 billion valuation to $965 billion inside the same quarter. Alphabet's private company holdings were worth about $124.3 billion on June 30, and the vast majority of that is Anthropic. Google cannot sell either position right now. Now trace where that valuation came from: Google started putting money into Anthropic in 2023. A $300 million bet has grown into a $13.3 billion position with commitments of up to $30 billion more. Anthropic committed to buying at least five gigawatts of computing capacity from Google Cloud. Google Cloud revenue then grew 82% to about $24.8 billion, the strongest quarter that business has ever had. That growth is part of the story the market uses to price both companies. And when Anthropic's valuation jumped, Google booked the jump as its OWN profit. Google is the investor, the supplier, and the party deciding what the asset is worth. A tax and accounting consultant named Robert Willens flagged this back in April, pointing out that Alphabet is able to influence the value of one of its own assets. And Alphabet's free cash flow for the quarter was negative $5.9 billion. That is the first negative quarter since Google went public in August 2004. Capital spending hit $44.9 billion. Operating cash flow was $39.1 billion. Capex now eats about 37.5% of every dollar of revenue, the highest share in the company's public life. To fund it, Alphabet has taken on roughly $100 billion of debt this year and raised about $85 billion in a June share sale, its first in more than two decades. This is a company that spent years buying its own stock back. What happens next: Alphabet raised 2026 capital spending guidance to between $195 billion and $205 billion, the second raise in three months. The finance chief told analysts 2027 spending will rise significantly. The company also disclosed $811 billion in contracted future spending commitments as of June, up nearly $500 billion from March. Those commitments are signed contracts that get paid in cash. The profit is an estimate of what a private company might be worth on a given day. Estimates move in both directions. If Anthropic or SpaceX gets repriced downward, the same line that produced the biggest quarter in Google's history runs backwards, and this quarter produced no free cash flow to absorb it. Meta, Microsoft and Amazon are all carrying their own private AI stakes into their own earnings reports. Watch how much of their profit they actually collected in cash...

Google just reported $99 billion in profits it never actually received. Alphabet posted net income of $112.1 billion for a single quarter. Earnings per share came in at $9.11 against a Wall Street estimate of $2.87. That is one of the largest profit quarters any company has ever printed. Yet the stock fell about 7% the same day. When people read past the headline and opened the earnings release, they found the reason sitting in one footnote... $99 billion of that profit came from a line called other income. Alphabet describes it as "primarily the result of net unrealized gains on our equity securities." So Google did not sell anything. It marked up shares it already owned and ran the increase through its income statement. That single line added $77.1 billion to net income after tax. It accounted for $6.26 of the $9.11 in earnings per share. Strip it out and adjusted earnings per share were $2.85. Analysts wanted $2.89. The ACTUAL business missed. Now here is what makes this insane: Most of that $99 billion came from two holdings, SpaceX and Anthropic. SpaceX went public on June 12 at roughly $1.77 trillion, up from about $400 billion a year earlier. Alphabet's stake is worth $94.1 billion, and roughly $80 billion of it sits under sale restrictions. Anthropic went from a $350 billion valuation to $965 billion inside the same quarter. Alphabet's private company holdings were worth about $124.3 billion on June 30, and the vast majority of that is Anthropic. Google cannot sell either position right now. Now trace where that valuation came from: Google started putting money into Anthropic in 2023. A $300 million bet has grown into a $13.3 billion position with commitments of up to $30 billion more. Anthropic committed to buying at least five gigawatts of computing capacity from Google Cloud. Google Cloud revenue then grew 82% to about $24.8 billion, the strongest quarter that business has ever had. That growth is part of the story the market uses to price both companies. And when Anthropic's valuation jumped, Google booked the jump as its OWN profit. Google is the investor, the supplier, and the party deciding what the asset is worth. A tax and accounting consultant named Robert Willens flagged this back in April, pointing out that Alphabet is able to influence the value of one of its own assets. And Alphabet's free cash flow for the quarter was negative $5.9 billion. That is the first negative quarter since Google went public in August 2004. Capital spending hit $44.9 billion. Operating cash flow was $39.1 billion. Capex now eats about 37.5% of every dollar of revenue, the highest share in the company's public life. To fund it, Alphabet has taken on roughly $100 billion of debt this year and raised about $85 billion in a June share sale, its first in more than two decades. This is a company that spent years buying its own stock back. What happens next: Alphabet raised 2026 capital spending guidance to between $195 billion and $205 billion, the second raise in three months. The finance chief told analysts 2027 spending will rise significantly. The company also disclosed $811 billion in contracted future spending commitments as of June, up nearly $500 billion from March. Those commitments are signed contracts that get paid in cash. The profit is an estimate of what a private company might be worth on a given day. Estimates move in both directions. If Anthropic or SpaceX gets repriced downward, the same line that produced the biggest quarter in Google's history runs backwards, and this quarter produced no free cash flow to absorb it. Meta, Microsoft and Amazon are all carrying their own private AI stakes into their own earnings reports. Watch how much of their profit they actually collected in cash...

Ricardo

364,665 次观看 • 1 个月前

Big Tech just ran out of money building AI and what they're doing to cover it up should be illegal. Google, Amazon, Microsoft, and Meta are spending a combined $700 BILLION this year on AI infrastructure. This eats up 94% of their total operating cash flow. The richest companies in human history are almost broke. And instead of slowing down, they're covering it up with the biggest financial engineering operation since 2008: Google just sold $80 billion in stock to fund AI infrastructure. That was their first equity raise in 20 YEARS. The last time Google needed to sell stock, YouTube didn't even exist. Sundar Pichai admitted the thing keeping him up at night is "compute capacity." The company that prints $100 billion a year in ad revenue just told Wall Street it isn't enough anymore. Amazon's free cash flow is projected to go NEGATIVE this year for the first time ever. Morgan Stanley estimates a $17 billion deficit and Bank of America says $28 billion. The most profitable logistics machine on Earth is about to burn more cash than it generates, and they quietly filed with the SEC saying they may need to raise even more debt and equity to keep building. All four hyperscalers are now borrowing hundreds of billions in bonds to keep the AI buildout alive. These were the most cash-rich companies in human history, and they're leveraging themselves to the teeth to build infrastructure that nobody has proven will generate enough revenue to pay for itself. And the cracks are already starting to show: Broadcom makes the custom AI chips that power Google, Meta, OpenAI, and Anthropic. This week their AI revenue TRIPLED year over year, sales grew 48%, and profits smashed every Wall Street estimate. The reward for all of that was $320 billion in value erased in a single trading session. Their CEO Hock Tan went on the earnings call and exposed three things about the AI industry: Google is already shopping for cheaper AI chip alternatives, broadcom abandoned its strategy of selling complete AI systems and is now retreating to selling bare chips at lower margins. And despite supposedly "unprecedented demand," Tan refused to raise his full-year forecast, which tells you everything about what he's actually seeing behind the curtain. Wall Street heard all three and hit the sell button so hard it dragged AMD, Intel, and the entire chip sector down with it. When a company triples its AI revenue and gets punished because tripling isn't fast enough, the expectations have left the atmosphere entirely. And here's the really scary part... These companies ARE your retirement account. Apple, Microsoft, Amazon, Google, Meta, and Nvidia make up roughly 30% of the S&P 500. If you have a 401k or an index fund, you are already exposed to this bet whether you chose to be or not. Every single one of these companies is telling you AI will generate trillions in revenue. But right now the math says they're spending trillions FIRST and hoping the revenue shows up later. If the revenue catches up, this becomes the greatest infrastructure buildout in human history. Bigger than railroads and bigger than the internet. If it doesn't, the companies that make up a third of the American stock market just leveraged their balance sheets into the largest write-down cycle since 2000. And unlike the dot-com crash, this time the bubble companies aren't random startups with no revenue. They're the backbone of the entire global economy.

Big Tech just ran out of money building AI and what they're doing to cover it up should be illegal. Google, Amazon, Microsoft, and Meta are spending a combined $700 BILLION this year on AI infrastructure. This eats up 94% of their total operating cash flow. The richest companies in human history are almost broke. And instead of slowing down, they're covering it up with the biggest financial engineering operation since 2008: Google just sold $80 billion in stock to fund AI infrastructure. That was their first equity raise in 20 YEARS. The last time Google needed to sell stock, YouTube didn't even exist. Sundar Pichai admitted the thing keeping him up at night is "compute capacity." The company that prints $100 billion a year in ad revenue just told Wall Street it isn't enough anymore. Amazon's free cash flow is projected to go NEGATIVE this year for the first time ever. Morgan Stanley estimates a $17 billion deficit and Bank of America says $28 billion. The most profitable logistics machine on Earth is about to burn more cash than it generates, and they quietly filed with the SEC saying they may need to raise even more debt and equity to keep building. All four hyperscalers are now borrowing hundreds of billions in bonds to keep the AI buildout alive. These were the most cash-rich companies in human history, and they're leveraging themselves to the teeth to build infrastructure that nobody has proven will generate enough revenue to pay for itself. And the cracks are already starting to show: Broadcom makes the custom AI chips that power Google, Meta, OpenAI, and Anthropic. This week their AI revenue TRIPLED year over year, sales grew 48%, and profits smashed every Wall Street estimate. The reward for all of that was $320 billion in value erased in a single trading session. Their CEO Hock Tan went on the earnings call and exposed three things about the AI industry: Google is already shopping for cheaper AI chip alternatives, broadcom abandoned its strategy of selling complete AI systems and is now retreating to selling bare chips at lower margins. And despite supposedly "unprecedented demand," Tan refused to raise his full-year forecast, which tells you everything about what he's actually seeing behind the curtain. Wall Street heard all three and hit the sell button so hard it dragged AMD, Intel, and the entire chip sector down with it. When a company triples its AI revenue and gets punished because tripling isn't fast enough, the expectations have left the atmosphere entirely. And here's the really scary part... These companies ARE your retirement account. Apple, Microsoft, Amazon, Google, Meta, and Nvidia make up roughly 30% of the S&P 500. If you have a 401k or an index fund, you are already exposed to this bet whether you chose to be or not. Every single one of these companies is telling you AI will generate trillions in revenue. But right now the math says they're spending trillions FIRST and hoping the revenue shows up later. If the revenue catches up, this becomes the greatest infrastructure buildout in human history. Bigger than railroads and bigger than the internet. If it doesn't, the companies that make up a third of the American stock market just leveraged their balance sheets into the largest write-down cycle since 2000. And unlike the dot-com crash, this time the bubble companies aren't random startups with no revenue. They're the backbone of the entire global economy.

Ricardo

228,416 次观看 • 3 个月前

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.

Ricardo

162,447 次观看 • 4 个月前

Chamath Palihapitiya just laid out the most important valuation question nobody on Wall Street wants to answer. For 20 years, the Mag 7 won because they had the greatest business model ever invented, asset- ight software. You write the code once, you sell it to a billion people, the marginal cost of the next customer is basically zero. There is essentially no factories, no raw materials, no union workers, no physical infrastructure, just pure leverage, scale the revenue, barely scale the costs. That's how you get 30x, 50x, 60x earnings multiples and the market was paying for compounding economics that had no natural ceiling. But AI just blew that model up. The hyperscalers, Amazon, Microsoft, Google, Meta are now projected to spend between $600 and $725 billion on capex in 2026 alone, up from $250 billion just two years ago. That number is climbing, not plateauing and it's not just the chips and the data centers, it's the energy contracts underneath all of it. When Microsoft re signed Three Mile Island, they locked in a 20 year forward purchase agreement at more than $100 per megawatt hour nearly double the prevailing spot rate of $60 for wind and solar in the same region. That's a long term liability commitment baked into operating cash flows for two decades. Here's where Chamath's math gets uncomfortable. These five or six companies are now collectively spending so much that their capex has exceeded their free cash flow meaning they can no longer self fund growth from operations alone. In 2025 alone, hyperscalers raised $108 billion in new debt and projections put the total debt issuance over the next few years at $1.5 trillion. These are companies that, for two decades, were net cash accumulators and now they're going to the debt markets like everyone else with term loans, revolvers, and structured credit facilities. That's Chamath's core point and it's a devastating one for anyone still modeling these companies the old way. When a company is asset light, investors pay a premium for that lightness and the multiple reflects the belief that returns on capital will stay high indefinitely, because there's no heavy physical plant dragging them down. But when Google starts looking like a utility locked into 20-year energy contracts, carrying hundreds of billions in debt, spending half its revenue on physical infrastructure, the rational multiple compresses. You don't price a utility at 30x earnings, you price it at 12x. His conclusion is that stop trying to value the hyperscalers themselves and follow the money instead. A trillion dollars a year is flowing out of these companies into power companies, data center operators, chip manufacturers, cooling systems, fiber networks, rare earth metals. The companies on the receiving end of that spending are already underpriced because the market is still staring at the senders while ignoring who's cashing the checks. The asset-light era minted the most valuable companies in human history and the asset heavy era that's replacing it might be the best argument yet for owning everything around them instead.

Chamath Palihapitiya just laid out the most important valuation question nobody on Wall Street wants to answer. For 20 years, the Mag 7 won because they had the greatest business model ever invented, asset- ight software. You write the code once, you sell it to a billion people, the marginal cost of the next customer is basically zero. There is essentially no factories, no raw materials, no union workers, no physical infrastructure, just pure leverage, scale the revenue, barely scale the costs. That's how you get 30x, 50x, 60x earnings multiples and the market was paying for compounding economics that had no natural ceiling. But AI just blew that model up. The hyperscalers, Amazon, Microsoft, Google, Meta are now projected to spend between $600 and $725 billion on capex in 2026 alone, up from $250 billion just two years ago. That number is climbing, not plateauing and it's not just the chips and the data centers, it's the energy contracts underneath all of it. When Microsoft re signed Three Mile Island, they locked in a 20 year forward purchase agreement at more than $100 per megawatt hour nearly double the prevailing spot rate of $60 for wind and solar in the same region. That's a long term liability commitment baked into operating cash flows for two decades. Here's where Chamath's math gets uncomfortable. These five or six companies are now collectively spending so much that their capex has exceeded their free cash flow meaning they can no longer self fund growth from operations alone. In 2025 alone, hyperscalers raised $108 billion in new debt and projections put the total debt issuance over the next few years at $1.5 trillion. These are companies that, for two decades, were net cash accumulators and now they're going to the debt markets like everyone else with term loans, revolvers, and structured credit facilities. That's Chamath's core point and it's a devastating one for anyone still modeling these companies the old way. When a company is asset light, investors pay a premium for that lightness and the multiple reflects the belief that returns on capital will stay high indefinitely, because there's no heavy physical plant dragging them down. But when Google starts looking like a utility locked into 20-year energy contracts, carrying hundreds of billions in debt, spending half its revenue on physical infrastructure, the rational multiple compresses. You don't price a utility at 30x earnings, you price it at 12x. His conclusion is that stop trying to value the hyperscalers themselves and follow the money instead. A trillion dollars a year is flowing out of these companies into power companies, data center operators, chip manufacturers, cooling systems, fiber networks, rare earth metals. The companies on the receiving end of that spending are already underpriced because the market is still staring at the senders while ignoring who's cashing the checks. The asset-light era minted the most valuable companies in human history and the asset heavy era that's replacing it might be the best argument yet for owning everything around them instead.

Milk Road AI

269,013 次观看 • 4 个月前

$In 45 years on Wall Street, I've never seen anything like this. Sam Altman just convinced 3 of the world's smartest investors to fund his losses. $110 billion. But ZERO profit in sight. The largest private funding round in history. Let me explain why this is borderline criminal & what you have to understand as an investor: Amazon. Nvidia. SoftBank. 3 of the world's most sophisticated investors just handed OpenAI $110 billion at an $840 billion valuation. That's more than double the $40 billion OpenAI raised last year. For context: all US venture capital combined invested $170 billion into American startups in all of 2023. Altman just raised 65% of that. Alone. In one round. And the company STILL isn't profitable. Let's look at the actual numbers: OpenAI burned $8 billion in 2025. They project burning $17 billion in 2026. $35 billion in 2027. $47 billion in 2028. Cumulative losses before any projected path to profitability: over $115 billion. Meanwhile, Amazon's $50 billion comes with strings attached. $35 billion is contingent on OpenAI either achieving AGI or completing its IPO by year end. Read that again. $35 billion is conditioned on ACHIEVING AGI. They're literally writing checks against a scientific breakthrough that may not happen on any predictable timeline. This is what peak cycle financing looks like. The circular logic every investor should understand: Amazon invests $50 billion in OpenAI. OpenAI commits to spending $100 billion on Amazon Web Services. Nvidia invests $30 billion. OpenAI commits to buying 3 gigawatts of Nvidia compute. These aren't arms-length investments. They're vendor financing dressed up as venture capital. Amazon and Nvidia are essentially paying OpenAI to buy their own products. The $840 billion valuation prices in a future that doesn't exist yet. At $13 billion in 2025 revenue, that's 65x revenue. Even in 2021 - the most speculative bubble in recent tech history - Snowflake peaked at 50-80x revenue. And Snowflake was actually profitable. J.P. Morgan calculates that the AI industry needs $650 billion in annual revenue just to generate a 10% return on total infrastructure buildout. The entire industry currently generates a fraction of that. I've seen cycles my entire 45-year career. The 1980s defense build-up. The dot-com bubble. The 2008 mortgage machine. The pattern is always the same: When the biggest players start financing each other's growth through circular investment structures, you're not witnessing a revolution... You're watching the LAST PHASE of a credit cycle. Amazon CEO Andy Jassy said OpenAI is going to be "one of the very big winners long term." Maybe. But $840 billion assumes they've already won. Stock prices follow earnings. Always have. Always will. And right now, OpenAI's earnings are deeply, structurally, massively negative. The IPO is coming. The hype will peak. And the question every serious investor needs to answer is simple: At what price does this actually make sense? Sam Altman doesn’t know either - he just keeps raising money faster than he can burn it. This can’t end well.$

In 45 years on Wall Street, I've never seen anything like this. Sam Altman just convinced 3 of the world's smartest investors to fund his losses. $110 billion. But ZERO profit in sight. The largest private funding round in history. Let me explain why this is borderline criminal & what you have to understand as an investor: Amazon. Nvidia. SoftBank. 3 of the world's most sophisticated investors just handed OpenAI $110 billion at an $840 billion valuation. That's more than double the $40 billion OpenAI raised last year. For context: all US venture capital combined invested $170 billion into American startups in all of 2023. Altman just raised 65% of that. Alone. In one round. And the company STILL isn't profitable. Let's look at the actual numbers: OpenAI burned $8 billion in 2025. They project burning $17 billion in 2026. $35 billion in 2027. $47 billion in 2028. Cumulative losses before any projected path to profitability: over $115 billion. Meanwhile, Amazon's $50 billion comes with strings attached. $35 billion is contingent on OpenAI either achieving AGI or completing its IPO by year end. Read that again. $35 billion is conditioned on ACHIEVING AGI. They're literally writing checks against a scientific breakthrough that may not happen on any predictable timeline. This is what peak cycle financing looks like. The circular logic every investor should understand: Amazon invests $50 billion in OpenAI. OpenAI commits to spending $100 billion on Amazon Web Services. Nvidia invests $30 billion. OpenAI commits to buying 3 gigawatts of Nvidia compute. These aren't arms-length investments. They're vendor financing dressed up as venture capital. Amazon and Nvidia are essentially paying OpenAI to buy their own products. The $840 billion valuation prices in a future that doesn't exist yet. At $13 billion in 2025 revenue, that's 65x revenue. Even in 2021 - the most speculative bubble in recent tech history - Snowflake peaked at 50-80x revenue. And Snowflake was actually profitable. J.P. Morgan calculates that the AI industry needs $650 billion in annual revenue just to generate a 10% return on total infrastructure buildout. The entire industry currently generates a fraction of that. I've seen cycles my entire 45-year career. The 1980s defense build-up. The dot-com bubble. The 2008 mortgage machine. The pattern is always the same: When the biggest players start financing each other's growth through circular investment structures, you're not witnessing a revolution... You're watching the LAST PHASE of a credit cycle. Amazon CEO Andy Jassy said OpenAI is going to be "one of the very big winners long term." Maybe. But $840 billion assumes they've already won. Stock prices follow earnings. Always have. Always will. And right now, OpenAI's earnings are deeply, structurally, massively negative. The IPO is coming. The hype will peak. And the question every serious investor needs to answer is simple: At what price does this actually make sense? Sam Altman doesn’t know either - he just keeps raising money faster than he can burn it. This can’t end well.

George Noble

1,198,005 次观看 • 6 个月前

Big Tech just forced the US government into bailing ITSELF out. This morning the US Treasury announced it will at least double the size of its own bond buybacks, because for two months almost nobody else wanted them. The 30-year Treasury bond hit its highest yield since 2007 last Thursday, then did it again yesterday. The long end has been in a buyers' strike since late June, meaning the pension funds and insurers who normally absorb 20 and 30 year government paper stopped showing up. This morning it auctioned $16 billion of 20-year debt at the second-worst yield since that bond was reintroduced in 2020. So the Treasury tore up a schedule it had published two weeks earlier. It doubled the maximum size of each long-bond buyback from $2 billion to at least $4 billion, and went from two operations a quarter to four. The 30-year yield fell 9 basis points within minutes. Stocks rallied. By early afternoon the 10-year had given almost all of it back. BUT the thing is, this operation changes almost nothing, because the underlying problem is untouched: The tidal wave of hyperscaler debt sitting on top of very large government deficits. Hyperscaler means Google, Meta, Microsoft, Amazon, Oracle and Nvidia. The Wall Street Journal went through the footnotes of 9 tech companies' filings on Sunday and found roughly $3 TRILLION in AI commitments sitting outside their balance sheets. That is 5x the $600 billion of capital spending those same companies reported over the past year. Alphabet alone discloses $811 billion in purchase and contractual obligations. Three months earlier it was $332 billion. All of it has to be funded somewhere. And this is where it collides with the government: Data centers, chip supply agreements and 20-year power contracts are long-duration assets, and long-duration assets get financed with long-duration debt. That is the exact product the US Treasury sells. There is a finite pool of investors willing to lend money for 30 years at a fixed rate. That pool does not get bigger because Meta needs another campus in Louisiana. So when the largest companies in history issue hundreds of billions of long-dated debt at the same moment the Treasury needs to roll a national debt approaching $40 trillion, both sides are bidding for the SAME buyers. One of those bidders can offer whatever yield it takes and book it as growth. The other one is the US government, and this morning it folded. Treasury does not create money for these buybacks. It funds them by issuing shorter-dated debt instead, so the obligation does not disappear. It gets pulled closer to the present, to be refinanced at whatever rate exists in a year or two. The government is buying back the debt nobody wants by selling more of the debt people still take. The 30-year Treasury yield is the number that prices your mortgage. The average 30-year fixed sits at 6.67% today. But there IS a real argument on the other side: Buybacks are routine, and $4 billion is nothing against a $30 trillion market. Plenty of serious people will call today housekeeping. But housekeeping shouldn’t require tearing up your own published schedule two weeks after you release it. The AI buildout is now financed at a scale that competes with sovereign borrowing, and the sovereign is losing bidders. Nobody voted on that, and people will pay for it in their mortgage rate long before anyone calls it a crisis. What do you think?

Big Tech just forced the US government into bailing ITSELF out. This morning the US Treasury announced it will at least double the size of its own bond buybacks, because for two months almost nobody else wanted them. The 30-year Treasury bond hit its highest yield since 2007 last Thursday, then did it again yesterday. The long end has been in a buyers' strike since late June, meaning the pension funds and insurers who normally absorb 20 and 30 year government paper stopped showing up. This morning it auctioned $16 billion of 20-year debt at the second-worst yield since that bond was reintroduced in 2020. So the Treasury tore up a schedule it had published two weeks earlier. It doubled the maximum size of each long-bond buyback from $2 billion to at least $4 billion, and went from two operations a quarter to four. The 30-year yield fell 9 basis points within minutes. Stocks rallied. By early afternoon the 10-year had given almost all of it back. BUT the thing is, this operation changes almost nothing, because the underlying problem is untouched: The tidal wave of hyperscaler debt sitting on top of very large government deficits. Hyperscaler means Google, Meta, Microsoft, Amazon, Oracle and Nvidia. The Wall Street Journal went through the footnotes of 9 tech companies' filings on Sunday and found roughly $3 TRILLION in AI commitments sitting outside their balance sheets. That is 5x the $600 billion of capital spending those same companies reported over the past year. Alphabet alone discloses $811 billion in purchase and contractual obligations. Three months earlier it was $332 billion. All of it has to be funded somewhere. And this is where it collides with the government: Data centers, chip supply agreements and 20-year power contracts are long-duration assets, and long-duration assets get financed with long-duration debt. That is the exact product the US Treasury sells. There is a finite pool of investors willing to lend money for 30 years at a fixed rate. That pool does not get bigger because Meta needs another campus in Louisiana. So when the largest companies in history issue hundreds of billions of long-dated debt at the same moment the Treasury needs to roll a national debt approaching $40 trillion, both sides are bidding for the SAME buyers. One of those bidders can offer whatever yield it takes and book it as growth. The other one is the US government, and this morning it folded. Treasury does not create money for these buybacks. It funds them by issuing shorter-dated debt instead, so the obligation does not disappear. It gets pulled closer to the present, to be refinanced at whatever rate exists in a year or two. The government is buying back the debt nobody wants by selling more of the debt people still take. The 30-year Treasury yield is the number that prices your mortgage. The average 30-year fixed sits at 6.67% today. But there IS a real argument on the other side: Buybacks are routine, and $4 billion is nothing against a $30 trillion market. Plenty of serious people will call today housekeeping. But housekeeping shouldn’t require tearing up your own published schedule two weeks after you release it. The AI buildout is now financed at a scale that competes with sovereign borrowing, and the sovereign is losing bidders. Nobody voted on that, and people will pay for it in their mortgage rate long before anyone calls it a crisis. What do you think?

Ricardo

60,135 次观看 • 1 个月前

PROOF THAT AI IS A PONZI SCHEME (and why it's the reason for Bitcoin's crash): Nvidia just posted the most insane earnings in tech history. $31.9 billion in profit. $57 billion in revenue. 65% profit jump year-over-year. Stock rallied immediately. Then 18 hours later, it dropped 5%. And when people looked closer at the numbers, they found something absolutely wild... The Unpaid Bills Nobody Talked About: Nvidia's accounts receivable jumped to $33.4 billion. That's up 89% in one year. Translation: $33 billion worth of "sales" that haven't been paid yet. The average wait time for payment went from 46 days to 53 days. That extra week of waiting? $10.4 billion that may never turn into actual cash. They're booking revenue. But customers aren't paying. The Inventory That Shouldn't Exist: Unsold chip inventory surged 32% in three months to $19.8 billion. Meanwhile, Nvidia's CEO keeps saying demand is "insane" and they can't make chips fast enough. If demand is so crazy, why is inventory piling up? Either customers aren't buying with cash, or the demand story is bullshit. The Profit vs Cash Problem: Nvidia reported $19.3 billion in profit. But only generated $14.5 billion in actual cash flow. That's a $4.8 billion gap. Their profit-to-cash conversion is 75%. TSMC and AMD? Over 95%. When profit doesn't turn into cash, something's wrong. Here's Where It Gets Insane: The money is going in circles. And the same dollars are being counted as revenue multiple times. Follow this: - Nvidia gave xAI $2 billion - xAI borrowed $12.5 billion to buy Nvidia chips - Microsoft invested $13 billion in OpenAI - OpenAI committed $50 billion to Microsoft's cloud - Microsoft ordered $100 billion in Nvidia chips for that cloud - Oracle gave OpenAI $300 billion in cloud credits - OpenAI used those credits to order Nvidia chips for Oracle data centers The money goes in a circle. Nvidia → xAI → Nvidia Microsoft → OpenAI → Microsoft → Nvidia Oracle → OpenAI → Oracle → Nvidia Everyone books revenue. Nobody's actually paying cash. It's financial engineering disguised as growth. The Smart Money Already Left: Peter Thiel sold his Nvidia stake. SoftBank dumped massive positions. Michael Burry (the guy who called 2008) bought $1.1 billion in put options betting Nvidia crashes. They saw the numbers before everyone else did. And they got out. The Bitcoin Collapse: Bitcoin crashed almost 30% from $126,000 to $89,567. Why does this matter? AI startups use Bitcoin as collateral for loans. If Nvidia's crisis deepens, those startups get margin called. They're forced to sell Bitcoin to cover. Which crashes Bitcoin further. Which triggers more margin calls. Analysts think it could hit $52,000 if this unravels. The MIT Reality Check: OpenAI is valued at $157 billion. MIT released a study saying 95% of AI projects will never be profitable. Not "might struggle." NEVER be profitable. The entire sector is built on inflated expectations. What Happens Next: February 2026: Nvidia's Q4 report shows how many bills are 60+ days overdue. March 2026: Credit agencies start downgrading Nvidia and related companies. April 2026: First earnings restatements hit. The whole thing unwinds. Some experts are calling this a Ponzi scheme. No formal fraud investigation yet. But the structure is there: - Use new investor money to pay old investors - Inflate revenue with circular deals - Book sales before receiving cash - Keep the music playing until someone asks for their money Nvidia executives deny everything. Say it's real growth. Real demand. Real transformation. But the numbers don't lie. $10.4 billion in delayed payments. $19.8 billion in unsold inventory. $4.8 billion profit-to-cash gap. Circular funding loops inflating revenue. This is either the biggest tech transformation in history, or the biggest financial engineering scam since 2008. The next three months will tell us which one it is. What are you betting on?

PROOF THAT AI IS A PONZI SCHEME (and why it's the reason for Bitcoin's crash): Nvidia just posted the most insane earnings in tech history. $31.9 billion in profit. $57 billion in revenue. 65% profit jump year-over-year. Stock rallied immediately. Then 18 hours later, it dropped 5%. And when people looked closer at the numbers, they found something absolutely wild... The Unpaid Bills Nobody Talked About: Nvidia's accounts receivable jumped to $33.4 billion. That's up 89% in one year. Translation: $33 billion worth of "sales" that haven't been paid yet. The average wait time for payment went from 46 days to 53 days. That extra week of waiting? $10.4 billion that may never turn into actual cash. They're booking revenue. But customers aren't paying. The Inventory That Shouldn't Exist: Unsold chip inventory surged 32% in three months to $19.8 billion. Meanwhile, Nvidia's CEO keeps saying demand is "insane" and they can't make chips fast enough. If demand is so crazy, why is inventory piling up? Either customers aren't buying with cash, or the demand story is bullshit. The Profit vs Cash Problem: Nvidia reported $19.3 billion in profit. But only generated $14.5 billion in actual cash flow. That's a $4.8 billion gap. Their profit-to-cash conversion is 75%. TSMC and AMD? Over 95%. When profit doesn't turn into cash, something's wrong. Here's Where It Gets Insane: The money is going in circles. And the same dollars are being counted as revenue multiple times. Follow this: - Nvidia gave xAI $2 billion - xAI borrowed $12.5 billion to buy Nvidia chips - Microsoft invested $13 billion in OpenAI - OpenAI committed $50 billion to Microsoft's cloud - Microsoft ordered $100 billion in Nvidia chips for that cloud - Oracle gave OpenAI $300 billion in cloud credits - OpenAI used those credits to order Nvidia chips for Oracle data centers The money goes in a circle. Nvidia → xAI → Nvidia Microsoft → OpenAI → Microsoft → Nvidia Oracle → OpenAI → Oracle → Nvidia Everyone books revenue. Nobody's actually paying cash. It's financial engineering disguised as growth. The Smart Money Already Left: Peter Thiel sold his Nvidia stake. SoftBank dumped massive positions. Michael Burry (the guy who called 2008) bought $1.1 billion in put options betting Nvidia crashes. They saw the numbers before everyone else did. And they got out. The Bitcoin Collapse: Bitcoin crashed almost 30% from $126,000 to $89,567. Why does this matter? AI startups use Bitcoin as collateral for loans. If Nvidia's crisis deepens, those startups get margin called. They're forced to sell Bitcoin to cover. Which crashes Bitcoin further. Which triggers more margin calls. Analysts think it could hit $52,000 if this unravels. The MIT Reality Check: OpenAI is valued at $157 billion. MIT released a study saying 95% of AI projects will never be profitable. Not "might struggle." NEVER be profitable. The entire sector is built on inflated expectations. What Happens Next: February 2026: Nvidia's Q4 report shows how many bills are 60+ days overdue. March 2026: Credit agencies start downgrading Nvidia and related companies. April 2026: First earnings restatements hit. The whole thing unwinds. Some experts are calling this a Ponzi scheme. No formal fraud investigation yet. But the structure is there: - Use new investor money to pay old investors - Inflate revenue with circular deals - Book sales before receiving cash - Keep the music playing until someone asks for their money Nvidia executives deny everything. Say it's real growth. Real demand. Real transformation. But the numbers don't lie. $10.4 billion in delayed payments. $19.8 billion in unsold inventory. $4.8 billion profit-to-cash gap. Circular funding loops inflating revenue. This is either the biggest tech transformation in history, or the biggest financial engineering scam since 2008. The next three months will tell us which one it is. What are you betting on?

Ricardo

212,902 次观看 • 10 个月前

🚨 THE WORLD’S CENTRAL BANKERS ARE STARTING TO PANIC ABOUT AI. Not because AI is failing. Because the entire AI boom is now being built on debt, leverage, shadow banking, and financial structures that are starting to look disturbingly similar to 2008. The BIS just warned that an “AI bust” could trigger serious global financial instability. And once you look at the numbers, the concern starts making sense very quickly. Amazon, Microsoft, Meta, Google and Oracle are expected to spend more than $1 TRILLION on AI capex between 2025 and 2026 alone. For 2026 itself, hyperscaler AI spending is tracking around $750 BILLION. That is a 77% jump from already record levels last year. The problem? A massive part of this expansion is being financed through debt. Morgan Stanley estimates hyperscalers and AI joint ventures alone could generate $250–300 BILLION in debt issuance by 2026. AI-focused companies already secured at least $200 BILLION through debt financing in 2025. And some companies are now literally borrowing money using Nvidia GPUs as collateral. That is where things start getting dangerous. CoreWeave, one of the biggest AI infrastructure companies, now has liabilities above $21 BILLION after pioneering GPU-backed debt financing. Its entire structure depends on Nvidia chips holding value long enough for the debt to get repaid. But GPUs depreciate extremely fast. Every new Nvidia generation immediately weakens the value of the previous one. Which means billions in loans are now backed by hardware that can lose relevance before the debt even matures. And according to the BIS, the financing structures around AI are becoming increasingly opaque. The same assets may be pledged multiple times across different financing vehicles. That is exactly the type of circular leverage that made the 2008 system so fragile. At the same time, the actual economic returns from AI still remain largely unproven. Goldman Sachs found “basically zero” economy-wide productivity gains from AI in 2025 despite hundreds of billions already being spent. Only 1% of S&P 500 companies were even able to quantify any earnings impact from AI. Yet markets are behaving like the returns are already guaranteed. Now combine this with: • Global debt at a record $353 TRILLION • Inflation jumping back to 4.2% • Private credit stress already appearing • AI chip shortages • Data center bottlenecks • And AI valuations approaching dot-com bubble extremes according to the IMF, ECB, BIS and Bank of England. This is why central banks are suddenly sounding alarmed. Because if hyperscalers ever slow AI spending, the debt chain behind the entire boom starts getting tested immediately. And right now, the global financial system is more leveraged than ever.

🚨 THE WORLD’S CENTRAL BANKERS ARE STARTING TO PANIC ABOUT AI. Not because AI is failing. Because the entire AI boom is now being built on debt, leverage, shadow banking, and financial structures that are starting to look disturbingly similar to 2008. The BIS just warned that an “AI bust” could trigger serious global financial instability. And once you look at the numbers, the concern starts making sense very quickly. Amazon, Microsoft, Meta, Google and Oracle are expected to spend more than $1 TRILLION on AI capex between 2025 and 2026 alone. For 2026 itself, hyperscaler AI spending is tracking around $750 BILLION. That is a 77% jump from already record levels last year. The problem? A massive part of this expansion is being financed through debt. Morgan Stanley estimates hyperscalers and AI joint ventures alone could generate $250–300 BILLION in debt issuance by 2026. AI-focused companies already secured at least $200 BILLION through debt financing in 2025. And some companies are now literally borrowing money using Nvidia GPUs as collateral. That is where things start getting dangerous. CoreWeave, one of the biggest AI infrastructure companies, now has liabilities above $21 BILLION after pioneering GPU-backed debt financing. Its entire structure depends on Nvidia chips holding value long enough for the debt to get repaid. But GPUs depreciate extremely fast. Every new Nvidia generation immediately weakens the value of the previous one. Which means billions in loans are now backed by hardware that can lose relevance before the debt even matures. And according to the BIS, the financing structures around AI are becoming increasingly opaque. The same assets may be pledged multiple times across different financing vehicles. That is exactly the type of circular leverage that made the 2008 system so fragile. At the same time, the actual economic returns from AI still remain largely unproven. Goldman Sachs found “basically zero” economy-wide productivity gains from AI in 2025 despite hundreds of billions already being spent. Only 1% of S&P 500 companies were even able to quantify any earnings impact from AI. Yet markets are behaving like the returns are already guaranteed. Now combine this with: • Global debt at a record $353 TRILLION • Inflation jumping back to 4.2% • Private credit stress already appearing • AI chip shortages • Data center bottlenecks • And AI valuations approaching dot-com bubble extremes according to the IMF, ECB, BIS and Bank of England. This is why central banks are suddenly sounding alarmed. Because if hyperscalers ever slow AI spending, the debt chain behind the entire boom starts getting tested immediately. And right now, the global financial system is more leveraged than ever.

Crypto Rover

86,404 次观看 • 2 个月前

Nebius will be a trillion dollar company (Save this). The neocloud market, purpose-built AI cloud infrastructure, separate from legacy hyperscalers generated roughly $25 billion in revenue in 2025, up 223% year over year. Synergy Research projects it will approach $400 billion by 2031, compounding at 58% annually one of the fastest sustained growth rates ever recorded for an infrastructure category of this scale. The CEO's explanation for why they win is worth understanding in detail. GPU compute is scarce and that part everyone knows but Nebius is not simply renting GPUs by the hour and marking them up, which is what most neocloud imitators do. They have built their own physical capacity for inference, optimized the full technology stack from the software layer all the way down to the rack hardware and recently acquired a company called Agen specifically to push inference latency even lower and throughput even higher. The CEO frames the core problem directly that in 2026, every product you build is powered by tokens, AI intelligence and while you can get those tokens from OpenAI or Anthropic via a simple API call, the moment you want to run open source models, specialized vertical models, or anything other than the two dominant frontier labs, you run into a wall. You can download the weights from Hugging Face and assemble the pieces. But getting those workloads to run at scale, at the economics you need, with the reliability your product requires, is an extraordinarily complex engineering challenge that most companies cannot staff or afford to solve in-house. That is the problem Nebius is solving, and that is why their inference product called Token Factory exists. The financial results are among the most dramatic growth numbers reported by any public company this year. In Q1 2026, Nebius posted $399 million in revenue, a 684% increase from the same quarter a year earlier. In the span of twelve months, the company swung from a $104 million net loss to $621 million in net income. Cash from operations went from negative $184 million to positive $2.26 billion in the same period meaning this is not growth funded by burning investor capital, it is growth that is now generating its own fuel. For the full year 2026, Nebius is guiding for an annualized revenue run rate of $7 billion to $9 billion, with pipeline creation tracking to surpass $4 billion. The contracted backlog sits at $49 billion, anchored by a $27 billion agreement with Meta, a deal worth up to $19.4 billion with Microsoft, and a public endorsement from Jensen Huang at NVIDIA's GTC conference in 2026. The current market cap is approximately $56 billion. A company with $7 to $9 billion in annualized revenue, growing at 684%, turning cash-flow positive, sitting on $49 billion in contracted backlog, operating in a market compounding at 58% annually toward $400 billion, that company has a credible path to 20x from its current valuation if execution holds. That is the trillion dollar case, and it does not require any heroic assumptions and it requires Nebius to keep doing what it is already demonstrably doing. Milk Road Pro called this one early. Our analysts added Nebius to the portfolio when it was still flying under the radar, and we are sitting on a massive gain on that position right now. If you want to see what else we are building conviction on before the rest of the market catches up, come join us at Milk Road Pro using the link below!

Nebius will be a trillion dollar company (Save this). The neocloud market, purpose-built AI cloud infrastructure, separate from legacy hyperscalers generated roughly $25 billion in revenue in 2025, up 223% year over year. Synergy Research projects it will approach $400 billion by 2031, compounding at 58% annually one of the fastest sustained growth rates ever recorded for an infrastructure category of this scale. The CEO's explanation for why they win is worth understanding in detail. GPU compute is scarce and that part everyone knows but Nebius is not simply renting GPUs by the hour and marking them up, which is what most neocloud imitators do. They have built their own physical capacity for inference, optimized the full technology stack from the software layer all the way down to the rack hardware and recently acquired a company called Agen specifically to push inference latency even lower and throughput even higher. The CEO frames the core problem directly that in 2026, every product you build is powered by tokens, AI intelligence and while you can get those tokens from OpenAI or Anthropic via a simple API call, the moment you want to run open source models, specialized vertical models, or anything other than the two dominant frontier labs, you run into a wall. You can download the weights from Hugging Face and assemble the pieces. But getting those workloads to run at scale, at the economics you need, with the reliability your product requires, is an extraordinarily complex engineering challenge that most companies cannot staff or afford to solve in-house. That is the problem Nebius is solving, and that is why their inference product called Token Factory exists. The financial results are among the most dramatic growth numbers reported by any public company this year. In Q1 2026, Nebius posted $399 million in revenue, a 684% increase from the same quarter a year earlier. In the span of twelve months, the company swung from a $104 million net loss to $621 million in net income. Cash from operations went from negative $184 million to positive $2.26 billion in the same period meaning this is not growth funded by burning investor capital, it is growth that is now generating its own fuel. For the full year 2026, Nebius is guiding for an annualized revenue run rate of $7 billion to $9 billion, with pipeline creation tracking to surpass $4 billion. The contracted backlog sits at $49 billion, anchored by a $27 billion agreement with Meta, a deal worth up to $19.4 billion with Microsoft, and a public endorsement from Jensen Huang at NVIDIA's GTC conference in 2026. The current market cap is approximately $56 billion. A company with $7 to $9 billion in annualized revenue, growing at 684%, turning cash-flow positive, sitting on $49 billion in contracted backlog, operating in a market compounding at 58% annually toward $400 billion, that company has a credible path to 20x from its current valuation if execution holds. That is the trillion dollar case, and it does not require any heroic assumptions and it requires Nebius to keep doing what it is already demonstrably doing. Milk Road Pro called this one early. Our analysts added Nebius to the portfolio when it was still flying under the radar, and we are sitting on a massive gain on that position right now. If you want to see what else we are building conviction on before the rest of the market catches up, come join us at Milk Road Pro using the link below!

Milk Road AI

28,622 次观看 • 4 个月前

THIS IS ABSOLUTELY RIDICULOUS. OpenAI and Anthropic are losing money on every dollar they make. OpenAI generated $20 billion in revenue in 2025 and is projected to lose $14 billion in the same year. Internal forecasts project cumulative losses hitting $44 billion by 2028. The company's own CFO warned executives in April 2026 that OpenAI might struggle to finance upcoming computing deals if revenue growth slows. Anthropic reached $4.3 billion in annualized revenue in April 2026 against $19 billion in total costs. It spends $3 to make $1, and is not expected to stop burning cash until 2027. Now look at what these two companies have committed to spend. OpenAI and Anthropic together have committed $1.05 trillion in cloud spending to Microsoft, Oracle, Google and Amazon, making up 43 to 54% of each provider's entire future revenue backlog. - Microsoft: $627B total backlog. OpenAI and Anthropic account for 49%. - Oracle: $553B total backlog. OpenAI alone accounts for 54%. - Google: $467.6B total backlog. Anthropic accounts for 43%. - Amazon: $464B total backlog. OpenAI and Anthropic account for 51%. The entire cloud industry's future revenue is a bet on two companies losing billions every quarter. Microsoft, Alphabet, Meta and Amazon are collectively expected to spend $725 billion in capex in 2026, almost entirely on AI infrastructure. Combined hyperscaler capex from 2025 to 2027 is projected at $1.15 trillion, more than double what was spent from 2022 to 2024. What is the return on all of this? McKinsey's 2025 State of AI survey found that only a minority of companies reported AI meaningfully increased revenue or reduced costs. Enterprise generative AI spending grew from $1.7 billion in 2023 to $37 billion in 2025 and most CIOs still describe their initiatives as pilots without clear ROI metrics. Microsoft's AI business is running at a $37 billion annual revenue run rate with 123% year over year growth. That sounds impressive until you realize most of the capex funding is justified by expected future AI revenue rather than current AI profit. The internet burned money for years before it became the most profitable industry in history. But right now $1 trillion in committed cloud spend, $725 billion in annual capex, two loss-making customers making up half of every major cloud provider's revenue backlog, and the enterprises writing the checks cannot tell you if any of it is working.

THIS IS ABSOLUTELY RIDICULOUS. OpenAI and Anthropic are losing money on every dollar they make. OpenAI generated $20 billion in revenue in 2025 and is projected to lose $14 billion in the same year. Internal forecasts project cumulative losses hitting $44 billion by 2028. The company's own CFO warned executives in April 2026 that OpenAI might struggle to finance upcoming computing deals if revenue growth slows. Anthropic reached $4.3 billion in annualized revenue in April 2026 against $19 billion in total costs. It spends $3 to make $1, and is not expected to stop burning cash until 2027. Now look at what these two companies have committed to spend. OpenAI and Anthropic together have committed $1.05 trillion in cloud spending to Microsoft, Oracle, Google and Amazon, making up 43 to 54% of each provider's entire future revenue backlog. - Microsoft: $627B total backlog. OpenAI and Anthropic account for 49%. - Oracle: $553B total backlog. OpenAI alone accounts for 54%. - Google: $467.6B total backlog. Anthropic accounts for 43%. - Amazon: $464B total backlog. OpenAI and Anthropic account for 51%. The entire cloud industry's future revenue is a bet on two companies losing billions every quarter. Microsoft, Alphabet, Meta and Amazon are collectively expected to spend $725 billion in capex in 2026, almost entirely on AI infrastructure. Combined hyperscaler capex from 2025 to 2027 is projected at $1.15 trillion, more than double what was spent from 2022 to 2024. What is the return on all of this? McKinsey's 2025 State of AI survey found that only a minority of companies reported AI meaningfully increased revenue or reduced costs. Enterprise generative AI spending grew from $1.7 billion in 2023 to $37 billion in 2025 and most CIOs still describe their initiatives as pilots without clear ROI metrics. Microsoft's AI business is running at a $37 billion annual revenue run rate with 123% year over year growth. That sounds impressive until you realize most of the capex funding is justified by expected future AI revenue rather than current AI profit. The internet burned money for years before it became the most profitable industry in history. But right now $1 trillion in committed cloud spend, $725 billion in annual capex, two loss-making customers making up half of every major cloud provider's revenue backlog, and the enterprises writing the checks cannot tell you if any of it is working.

Crypto Rover

58,862 次观看 • 4 个月前

$Elon Musk just told lenders he's paying back $17.5 BILLION in debt across X and xAI. Including $3 billion in high-yield bonds being redeemed early at 117 cents on the dollar. NOBODY knows where the money is coming from. And nobody seems to care. Let me explain why you should: Morgan Stanley has been calling existing lenders and telling them everything gets repaid in full. The X debt from the Twitter buyout. The xAI bonds from June. All of it. The bonds were structured to stay outstanding for at least 2 years. They're being called back less than a year later at a 17% premium. Bondholders are thrilled. Of course they are. They're getting paid above par on junk paper. But here's the part that should make you uncomfortable: xAI lost $1.46 billion in a single quarter last year. Burned through $7.8 billion in cash in the first 9 months of 2025. Revenue for the September quarter was $107 million. That's a company hemorrhaging roughly $1 billion a month. On a standalone basis, xAI exited 2025 at about a $500 million annualized revenue run rate. Even with optimistic projections, they might hit $2 billion in 2026. So where does $17.5 billion come from? xAI raised $20 billion in a Series E round in January. That's the most likely answer. Take the money investors gave you to build AI infrastructure and use a huge chunk of it to retire debt. But that's NOT a sign of strength. That's financial engineering. You raise $20 billion from investors who think they're funding the next frontier of artificial intelligence, then you turn around and use most of it to clean up the balance sheet before an IPO. Because that's what this is really about. SpaceX is targeting a confidential SEC filing as early as this month. IPO could come in June. Valuation targets exceed $1.75 trillion. The combined SpaceX-xAI entity currently carries about $18 billion in obligations. You can't take a $1.25 trillion company public with $18 billion in legacy debt from a money-losing AI startup and a social media platform that was acquired with leveraged buyout financing. So you nuke the debt. Clean the balance sheet. Present a simpler story to IPO investors. Smart? Absolutely. But let's be honest about what it actually is. SpaceX proper generated about $15 billion in revenue and $8 billion in profit in 2025. xAI generated roughly $250 million in six months and lost $2.5 billion doing it. At a $1.5 trillion IPO valuation, you're looking at roughly 94x trailing sales and 500x trailing earnings for the combined business. Those are not rational multiples. Those are lottery ticket multiples with better branding. And the $17.5 billion debt payoff doesn't change the underlying economics. It only changes the optics. xAI is still burning close to $1 billion a month. Grok still has a fraction of ChatGPT's market share. The revenue doesn't come close to justifying the infrastructure spend. What this reminds me of is the classic pre-IPO playbook taken to an extreme: Use private capital to dress up the financials, time the listing for maximum enthusiasm, and let public market investors hold the bag if execution falls short. The companies that need to clean house before going public are rarely the ones that reward you for buying on day one. My positioning hasn't changed. The AI infrastructure spending boom is real. But the returns aren't materializing for the companies actually deploying the technology. That gap between spending and results is where fortunes get destroyed. Stay skeptical. Stay disciplined. And remember: If the source of $17.5 billion in repayment capital is a mystery, it's a WARNING.$

Elon Musk just told lenders he's paying back $17.5 BILLION in debt across X and xAI. Including $3 billion in high-yield bonds being redeemed early at 117 cents on the dollar. NOBODY knows where the money is coming from. And nobody seems to care. Let me explain why you should: Morgan Stanley has been calling existing lenders and telling them everything gets repaid in full. The X debt from the Twitter buyout. The xAI bonds from June. All of it. The bonds were structured to stay outstanding for at least 2 years. They're being called back less than a year later at a 17% premium. Bondholders are thrilled. Of course they are. They're getting paid above par on junk paper. But here's the part that should make you uncomfortable: xAI lost $1.46 billion in a single quarter last year. Burned through $7.8 billion in cash in the first 9 months of 2025. Revenue for the September quarter was $107 million. That's a company hemorrhaging roughly $1 billion a month. On a standalone basis, xAI exited 2025 at about a $500 million annualized revenue run rate. Even with optimistic projections, they might hit $2 billion in 2026. So where does $17.5 billion come from? xAI raised $20 billion in a Series E round in January. That's the most likely answer. Take the money investors gave you to build AI infrastructure and use a huge chunk of it to retire debt. But that's NOT a sign of strength. That's financial engineering. You raise $20 billion from investors who think they're funding the next frontier of artificial intelligence, then you turn around and use most of it to clean up the balance sheet before an IPO. Because that's what this is really about. SpaceX is targeting a confidential SEC filing as early as this month. IPO could come in June. Valuation targets exceed $1.75 trillion. The combined SpaceX-xAI entity currently carries about $18 billion in obligations. You can't take a $1.25 trillion company public with $18 billion in legacy debt from a money-losing AI startup and a social media platform that was acquired with leveraged buyout financing. So you nuke the debt. Clean the balance sheet. Present a simpler story to IPO investors. Smart? Absolutely. But let's be honest about what it actually is. SpaceX proper generated about $15 billion in revenue and $8 billion in profit in 2025. xAI generated roughly $250 million in six months and lost $2.5 billion doing it. At a $1.5 trillion IPO valuation, you're looking at roughly 94x trailing sales and 500x trailing earnings for the combined business. Those are not rational multiples. Those are lottery ticket multiples with better branding. And the $17.5 billion debt payoff doesn't change the underlying economics. It only changes the optics. xAI is still burning close to $1 billion a month. Grok still has a fraction of ChatGPT's market share. The revenue doesn't come close to justifying the infrastructure spend. What this reminds me of is the classic pre-IPO playbook taken to an extreme: Use private capital to dress up the financials, time the listing for maximum enthusiasm, and let public market investors hold the bag if execution falls short. The companies that need to clean house before going public are rarely the ones that reward you for buying on day one. My positioning hasn't changed. The AI infrastructure spending boom is real. But the returns aren't materializing for the companies actually deploying the technology. That gap between spending and results is where fortunes get destroyed. Stay skeptical. Stay disciplined. And remember: If the source of $17.5 billion in repayment capital is a mystery, it's a WARNING.

George Noble

471,839 次观看 • 6 个月前

Big Tech is destroying American farmland to build $700 BILLION data centers filled with chips that will be worthless within 3 years. They're literally lying to you about what the math actually looks like: Nvidia releases a new chip architecture every two years and now ships upgrades annually within each generation. Every release makes the previous generation economically dead for cutting-edge AI. Jensen Huang literally said it on stage: "When Blackwell starts shipping in volume, you couldn't give Hoppers away." The next generation, Vera Rubin, ships later this year. 10x the performance per watt. 10x cheaper inference. A Princeton study found that GPUs running standard AI workloads physically survive one to two years, three at most, before thermal stress destroys them. So the chips die fast and become obsolete even faster. But here's the accounting trick that makes the whole thing look profitable: Microsoft, Google, Meta, and Amazon are depreciating these chips over 5 to 6 years on their books. They used to use 3 years but they extended the schedule right as AI spending exploded. Meta alone extended its depreciation timeline 3 separate times in 3 years, each extension conveniently boosting quarterly earnings by billions. If you depreciate a chip over 6 years but it becomes worthless in two, your reported profits are FAKE. You're spreading the cost over years where the asset generates zero value. Your earnings look incredible on paper while the actual hardware sits in a rack burning electricity for no economic reason. Michael Burry ran the numbers on this: He estimates that from 2026 to 2028, depreciation across the hyperscalers will be understated by $176 billion. That means these companies are overstating profits by over 20%. He put 79% of his final portfolio into bets AGAINST Nvidia and Palantir before shutting down his fund entirely. Now here's where it gets criminal... These data centers need to go somewhere. And Big Tech is shoving them into rural communities that have ZERO power to fight back. 67% of new data centers are being built outside cities on farmland and in small towns. Trump signed an executive order streamlining permitting for any project over $500 million, which effectively lets developers bypass local opposition entirely. A Michigan farm town just found out what that looks like in practice: Saline Township voted NO to a $16 billion OpenAI-Oracle data center. The board rejected it 4-1. But two days later, the developer sued. And the developer is Related Digital, founded by billionaire Stephen Ross, and one of its vice presidents is married to Michigan's Secretary of State who is now running for governor. The township couldn't afford a legal war against OpenAI, Oracle, and SoftBank. So they settled - and construction started immediately. Over 100 communities across 12 states have tried to block data center builds this year. Electricity rates are up 32% in 5 years. And every few years the entire computing infrastructure inside these buildings gets ripped out and replaced with the next generation, consuming more power, more water, and more of the local grid each cycle. The buildings are permanent, the disruption is permanent, but the chips are disposable. These towns are not hosting infrastructure. They're just absorbing the physical consequences of a financial model that needs permanent construction and permanent replacement to keep quarterly earnings looking right. The executives will simply move on and throw away the chips. But the damage will stay.

Big Tech is destroying American farmland to build $700 BILLION data centers filled with chips that will be worthless within 3 years. They're literally lying to you about what the math actually looks like: Nvidia releases a new chip architecture every two years and now ships upgrades annually within each generation. Every release makes the previous generation economically dead for cutting-edge AI. Jensen Huang literally said it on stage: "When Blackwell starts shipping in volume, you couldn't give Hoppers away." The next generation, Vera Rubin, ships later this year. 10x the performance per watt. 10x cheaper inference. A Princeton study found that GPUs running standard AI workloads physically survive one to two years, three at most, before thermal stress destroys them. So the chips die fast and become obsolete even faster. But here's the accounting trick that makes the whole thing look profitable: Microsoft, Google, Meta, and Amazon are depreciating these chips over 5 to 6 years on their books. They used to use 3 years but they extended the schedule right as AI spending exploded. Meta alone extended its depreciation timeline 3 separate times in 3 years, each extension conveniently boosting quarterly earnings by billions. If you depreciate a chip over 6 years but it becomes worthless in two, your reported profits are FAKE. You're spreading the cost over years where the asset generates zero value. Your earnings look incredible on paper while the actual hardware sits in a rack burning electricity for no economic reason. Michael Burry ran the numbers on this: He estimates that from 2026 to 2028, depreciation across the hyperscalers will be understated by $176 billion. That means these companies are overstating profits by over 20%. He put 79% of his final portfolio into bets AGAINST Nvidia and Palantir before shutting down his fund entirely. Now here's where it gets criminal... These data centers need to go somewhere. And Big Tech is shoving them into rural communities that have ZERO power to fight back. 67% of new data centers are being built outside cities on farmland and in small towns. Trump signed an executive order streamlining permitting for any project over $500 million, which effectively lets developers bypass local opposition entirely. A Michigan farm town just found out what that looks like in practice: Saline Township voted NO to a $16 billion OpenAI-Oracle data center. The board rejected it 4-1. But two days later, the developer sued. And the developer is Related Digital, founded by billionaire Stephen Ross, and one of its vice presidents is married to Michigan's Secretary of State who is now running for governor. The township couldn't afford a legal war against OpenAI, Oracle, and SoftBank. So they settled - and construction started immediately. Over 100 communities across 12 states have tried to block data center builds this year. Electricity rates are up 32% in 5 years. And every few years the entire computing infrastructure inside these buildings gets ripped out and replaced with the next generation, consuming more power, more water, and more of the local grid each cycle. The buildings are permanent, the disruption is permanent, but the chips are disposable. These towns are not hosting infrastructure. They're just absorbing the physical consequences of a financial model that needs permanent construction and permanent replacement to keep quarterly earnings looking right. The executives will simply move on and throw away the chips. But the damage will stay.

Ricardo

52,328 次观看 • 4 个月前

SUNDAR PICHAI: AI IS REWRITING EARTH’S INFRASTRUCTURE IN TWO YEARS Sundar laid it out with quiet certainty: the AI boom isn’t coming, it’s already rewriting the laws of scale: "You know, maybe four years ago Google was spending less than $30 billion per year. This year, that number is gonna be over $90 billion. And if you collectively add what all the companies are doing, we have well over a trillion dollars of investment going in, in building the infrastructure for this moment. And one way I think about it is in the next couple of years, we'll end up building what we probably built in the past 10 to 20 years. So hopefully just in a couple of years. So that gives you the scale at which this is ramping up." It’s the kind of scale that makes empires blink. Alphabet’s AI capex shot from $24 billion in 2021 to over $90 billion in 2025, powered by Gemini, Vertex AI, and an arms race for compute that’s now burning through a trillion dollars across Google, Microsoft, Amazon, and Meta. Source: thewizeai / Sundar Pichai

SUNDAR PICHAI: AI IS REWRITING EARTH’S INFRASTRUCTURE IN TWO YEARS Sundar laid it out with quiet certainty: the AI boom isn’t coming, it’s already rewriting the laws of scale: "You know, maybe four years ago Google was spending less than $30 billion per year. This year, that number is gonna be over $90 billion. And if you collectively add what all the companies are doing, we have well over a trillion dollars of investment going in, in building the infrastructure for this moment. And one way I think about it is in the next couple of years, we'll end up building what we probably built in the past 10 to 20 years. So hopefully just in a couple of years. So that gives you the scale at which this is ramping up." It’s the kind of scale that makes empires blink. Alphabet’s AI capex shot from $24 billion in 2021 to over $90 billion in 2025, powered by Gemini, Vertex AI, and an arms race for compute that’s now burning through a trillion dollars across Google, Microsoft, Amazon, and Meta. Source: thewizeai / Sundar Pichai

Mario Nawfal

163,412 次观看 • 9 个月前

Morgan Stanley just raised their 2027 AI capex forecast to $1.1 trillion and that number still doesn't include SpaceX or a lot of the other AI companies (Save this). When you factor those in, the real 2027 figure is probably closer to $1.5 trillion and AI lab inference revenue combined is tracking toward $300 billion in 2027. On its surface that ratio sounds alarming, spending $1.5 trillion in capex to generate $300 billion in revenue. But the framing collapses the moment you examine two things the bears consistently ignore, gross margins and the revenue trajectory. Gross margins on inference revenue are running at 60 to 70 percent. That means the $300 billion in inference revenue generates $180 to $210 billion in gross profit and that number compounds rapidly as utilization scales on infrastructure that is already built and paid for. The Capex is not being deployed against today's revenue but rather being deployed against a revenue trajectory that has shown no signs of decelerating. To understand how aggressive that trajectory actually is, consider that Morgan Stanley's $1.1 trillion hyperscaler forecast is nearly double what analysts projected for the same year just twelve months ago And they described the demand as inelastic, meaning it is not slowing down regardless of rising costs, tighter financing conditions or geopolitical risk. The AI industry ended 2025 tracking well over $200 billion in combined inference revenue and the growth rate since then has continued to accelerate rather than flatten. Anthropic alone scaled from negligible revenue to a $30 billion annualized run rate in approximately 18 months while OpenAI is tracking toward $280 billion in annual revenue by 2030 from $13 billion in 2025. There is also a structural reality in the capex number that the bears never account for. Roughly 35 percent of total AI spending goes toward training, building the next model generation which is not revenue-generating in the current period. That means only about 65 percent of the $1.5 trillion in capex is actually deployed against the inference infrastructure that earns revenue today. When you apply the 60 to 70 percent gross margin to the revenue that sits on top of that 65 percent figure, the economics look substantially better than the headline capex to revenue ratio implies. Every CEO who has been closest to this buildout has consistently underestimated it and Jensen Huang projected $1 trillion in AI capex two years ago and was called delusional. Dario Amodei said in early 2026 that AI revenues would reach the low hundreds of billions by 2028 and trillions before 2030 and given where Anthropic's own revenue trajectory is today, he is likely revising those numbers upward. The pattern here is consistent, every time someone models the revenue ceiling, the actual number breaks through it faster than expected. Come join Milk Road Pro for our full breakdown, the real unit economics of the AI inference buildout, how the capex to revenue ratio evolves over the next three years, and our entire AI thesis! Link below!

Morgan Stanley just raised their 2027 AI capex forecast to $1.1 trillion and that number still doesn't include SpaceX or a lot of the other AI companies (Save this). When you factor those in, the real 2027 figure is probably closer to $1.5 trillion and AI lab inference revenue combined is tracking toward $300 billion in 2027. On its surface that ratio sounds alarming, spending $1.5 trillion in capex to generate $300 billion in revenue. But the framing collapses the moment you examine two things the bears consistently ignore, gross margins and the revenue trajectory. Gross margins on inference revenue are running at 60 to 70 percent. That means the $300 billion in inference revenue generates $180 to $210 billion in gross profit and that number compounds rapidly as utilization scales on infrastructure that is already built and paid for. The Capex is not being deployed against today's revenue but rather being deployed against a revenue trajectory that has shown no signs of decelerating. To understand how aggressive that trajectory actually is, consider that Morgan Stanley's $1.1 trillion hyperscaler forecast is nearly double what analysts projected for the same year just twelve months ago And they described the demand as inelastic, meaning it is not slowing down regardless of rising costs, tighter financing conditions or geopolitical risk. The AI industry ended 2025 tracking well over $200 billion in combined inference revenue and the growth rate since then has continued to accelerate rather than flatten. Anthropic alone scaled from negligible revenue to a $30 billion annualized run rate in approximately 18 months while OpenAI is tracking toward $280 billion in annual revenue by 2030 from $13 billion in 2025. There is also a structural reality in the capex number that the bears never account for. Roughly 35 percent of total AI spending goes toward training, building the next model generation which is not revenue-generating in the current period. That means only about 65 percent of the $1.5 trillion in capex is actually deployed against the inference infrastructure that earns revenue today. When you apply the 60 to 70 percent gross margin to the revenue that sits on top of that 65 percent figure, the economics look substantially better than the headline capex to revenue ratio implies. Every CEO who has been closest to this buildout has consistently underestimated it and Jensen Huang projected $1 trillion in AI capex two years ago and was called delusional. Dario Amodei said in early 2026 that AI revenues would reach the low hundreds of billions by 2028 and trillions before 2030 and given where Anthropic's own revenue trajectory is today, he is likely revising those numbers upward. The pattern here is consistent, every time someone models the revenue ceiling, the actual number breaks through it faster than expected. Come join Milk Road Pro for our full breakdown, the real unit economics of the AI inference buildout, how the capex to revenue ratio evolves over the next three years, and our entire AI thesis! Link below!

Milk Road AI

21,141 次观看 • 3 个月前

Elon Musk's biggest competitor is secretly paying him $1.25 BILLION per month. SpaceX just revealed its financials for the first time in 23 years of existence. And buried deep in the S-1 is a detail that changes how you should think about the entire AI race. Anthropic, the company building Claude, the company that positions itself as OpenAI's biggest threat, the company valued at over $100 billion, is paying SpaceX $1.25 billion EVERY SINGLE MONTH for compute capacity through May 2029. That is $15 billion a year flowing directly from Elon's top AI competitor into Elon's bank account. Think about what that means: Every time Anthropic trains a new model, improves Claude, or lands an enterprise customer, a massive chunk of that revenue goes straight to the guy who owns the competing AI product. Anthropic is literally funding the war against itself. And that's just the beginning of what this filing reveals... The entire SpaceX IPO is structured around a bet most people haven't figured out yet. In 2025, SpaceX spent $20 billion in capex. 60% of that, roughly $12 billion, went to AI infrastructure. Rockets and satellites got the leftovers. In Q1 2026 alone, $7.7 billion out of $10 billion in total capex went to AI. The "rocket company" is spending like an AI company. Meanwhile, xAI, the division that houses Grok, generated $3.2 billion in revenue for the full year of 2025. But its R&D costs TRIPLED to $5 billion. It's burning cash at a pace that would have destroyed it as a standalone company. Which is exactly why Elon merged it into SpaceX two months before filing the IPO. And Starlink is the engine that makes the whole thing work: $11.4 billion in revenue, $4.4 billion in operating profit, and 10.3 million subscribers across 164 countries. It's one of the most profitable subscription businesses on the planet right now. But the average revenue per user DROPPED from $99 per month in 2023 to $66 per month in March 2026. Subscribers quadrupled but each one is paying a third less. Starlink is growing by getting cheaper. SpaceX has lost $37 BILLION since it was founded. Net loss in 2025 was $4.9 billion. This is a company that has never turned an annual profit in 23 years of operation, and it is about to IPO at a $1.75 trillion valuation. And the total addressable market SpaceX claims in the filing is $28.5 trillion. That is a QUARTER of global GDP. So here is what investors are actually buying when this IPO prices: They are buying the most profitable satellite internet business in history, stapled to an AI lab that is burning cash, wrapped inside a Mars colonization pitch that requires building a permanent city on another planet, funded by monthly billion-dollar payments from a direct competitor who has no other option for compute at that scale. This is the kind of thing only Elon could pull off.

Elon Musk's biggest competitor is secretly paying him $1.25 BILLION per month. SpaceX just revealed its financials for the first time in 23 years of existence. And buried deep in the S-1 is a detail that changes how you should think about the entire AI race. Anthropic, the company building Claude, the company that positions itself as OpenAI's biggest threat, the company valued at over $100 billion, is paying SpaceX $1.25 billion EVERY SINGLE MONTH for compute capacity through May 2029. That is $15 billion a year flowing directly from Elon's top AI competitor into Elon's bank account. Think about what that means: Every time Anthropic trains a new model, improves Claude, or lands an enterprise customer, a massive chunk of that revenue goes straight to the guy who owns the competing AI product. Anthropic is literally funding the war against itself. And that's just the beginning of what this filing reveals... The entire SpaceX IPO is structured around a bet most people haven't figured out yet. In 2025, SpaceX spent $20 billion in capex. 60% of that, roughly $12 billion, went to AI infrastructure. Rockets and satellites got the leftovers. In Q1 2026 alone, $7.7 billion out of $10 billion in total capex went to AI. The "rocket company" is spending like an AI company. Meanwhile, xAI, the division that houses Grok, generated $3.2 billion in revenue for the full year of 2025. But its R&D costs TRIPLED to $5 billion. It's burning cash at a pace that would have destroyed it as a standalone company. Which is exactly why Elon merged it into SpaceX two months before filing the IPO. And Starlink is the engine that makes the whole thing work: $11.4 billion in revenue, $4.4 billion in operating profit, and 10.3 million subscribers across 164 countries. It's one of the most profitable subscription businesses on the planet right now. But the average revenue per user DROPPED from $99 per month in 2023 to $66 per month in March 2026. Subscribers quadrupled but each one is paying a third less. Starlink is growing by getting cheaper. SpaceX has lost $37 BILLION since it was founded. Net loss in 2025 was $4.9 billion. This is a company that has never turned an annual profit in 23 years of operation, and it is about to IPO at a $1.75 trillion valuation. And the total addressable market SpaceX claims in the filing is $28.5 trillion. That is a QUARTER of global GDP. So here is what investors are actually buying when this IPO prices: They are buying the most profitable satellite internet business in history, stapled to an AI lab that is burning cash, wrapped inside a Mars colonization pitch that requires building a permanent city on another planet, funded by monthly billion-dollar payments from a direct competitor who has no other option for compute at that scale. This is the kind of thing only Elon could pull off.

Ricardo

208,631 次观看 • 4 个月前

Wall Street just pulled off the exact move that turned 2008 from a housing problem into a global collapse. They turned Nvidia graphics cards into bonds, stamped them investment grade, and started selling them into the funds that hold retirement money. Here is what happened while everyone was busy arguing about whether AI stocks were overvalued: The company at the center is CoreWeave, which rents out Nvidia chips to AI companies. To buy those chips, it borrows enormous sums, and the collateral on the loans is the chips themselves. That alone is alarming because a graphics card LOSES most of its value within a few years as the next generation makes it obsolete. You are lending against an asset built to rot. In January, Nvidia invested $2 billion straight into CoreWeave, which then used borrowed money to buy more Nvidia chips. On March 31, CoreWeave closed an $8.5 billion loan backed by its chips, and for the first time the rating agencies stamped that chip-backed debt investment grade, with Moody's assigning it an A3. Debt secured by depreciating graphics cards was rated nearly as SAFE as a blue-chip corporate bond. Then on May 18, CoreWeave closed the first chip-backed facility designed to be publicly syndicated and traded on secondary markets. And that's the part that really matters because it means this debt can now be sliced up, passed around, and bought by anyone, including the bond funds and pension managers who are required to hold "safe" investment-grade paper. On June 11, it announced another $3.5 billion in bonds on top of all of it. Now compare this to what happened in the past: Subprime mortgages in 2007 were not dangerous because some people got loans they couldn't repay... They became a global bomb the moment that debt got rated AAA and sold into the wider financial system, because the rating is what let it bleed into money market funds, pensions, and bank balance sheets that were supposed to be boring and safe. The bad loans were the spark but the packaging and rating were the detonator. And that detonator just got built for AI. Debt backed by graphics cards is now rated investment grade and trades on secondary markets, which means the AI bubble is no longer trapped inside tech stocks you can choose not to own. It has been quietly converted into bonds and routed toward the retirement accounts of people who have never typed a single prompt in their lives. And the whole structure rests on a backlog of customer "commitments" that CoreWeave values at nearly $100 BILLION, backed by a $21 billion Meta deal and a $6 billion Jane Street deal. Those are promises to pay over many years, made by AI companies that are themselves mostly unprofitable and burning cash. If even a few of those customers slow down or walk away, the collateral sitting under all this rated debt is a warehouse of chips losing value by the month. The AI bubble used to be a stock-market story you could opt out of. But as of this spring, that isn't the case anymore. So here's the real question: When the people packaging this debt swear to you that it's safe, who do you think is standing on the other side of that trade?

Wall Street just pulled off the exact move that turned 2008 from a housing problem into a global collapse. They turned Nvidia graphics cards into bonds, stamped them investment grade, and started selling them into the funds that hold retirement money. Here is what happened while everyone was busy arguing about whether AI stocks were overvalued: The company at the center is CoreWeave, which rents out Nvidia chips to AI companies. To buy those chips, it borrows enormous sums, and the collateral on the loans is the chips themselves. That alone is alarming because a graphics card LOSES most of its value within a few years as the next generation makes it obsolete. You are lending against an asset built to rot. In January, Nvidia invested $2 billion straight into CoreWeave, which then used borrowed money to buy more Nvidia chips. On March 31, CoreWeave closed an $8.5 billion loan backed by its chips, and for the first time the rating agencies stamped that chip-backed debt investment grade, with Moody's assigning it an A3. Debt secured by depreciating graphics cards was rated nearly as SAFE as a blue-chip corporate bond. Then on May 18, CoreWeave closed the first chip-backed facility designed to be publicly syndicated and traded on secondary markets. And that's the part that really matters because it means this debt can now be sliced up, passed around, and bought by anyone, including the bond funds and pension managers who are required to hold "safe" investment-grade paper. On June 11, it announced another $3.5 billion in bonds on top of all of it. Now compare this to what happened in the past: Subprime mortgages in 2007 were not dangerous because some people got loans they couldn't repay... They became a global bomb the moment that debt got rated AAA and sold into the wider financial system, because the rating is what let it bleed into money market funds, pensions, and bank balance sheets that were supposed to be boring and safe. The bad loans were the spark but the packaging and rating were the detonator. And that detonator just got built for AI. Debt backed by graphics cards is now rated investment grade and trades on secondary markets, which means the AI bubble is no longer trapped inside tech stocks you can choose not to own. It has been quietly converted into bonds and routed toward the retirement accounts of people who have never typed a single prompt in their lives. And the whole structure rests on a backlog of customer "commitments" that CoreWeave values at nearly $100 BILLION, backed by a $21 billion Meta deal and a $6 billion Jane Street deal. Those are promises to pay over many years, made by AI companies that are themselves mostly unprofitable and burning cash. If even a few of those customers slow down or walk away, the collateral sitting under all this rated debt is a warehouse of chips losing value by the month. The AI bubble used to be a stock-market story you could opt out of. But as of this spring, that isn't the case anymore. So here's the real question: When the people packaging this debt swear to you that it's safe, who do you think is standing on the other side of that trade?

Ricardo

212,317 次观看 • 3 个月前