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SITUATION EXPLAINED: OpenAI is leasing a 10-gigawatt data center. • Largest operational data centers today: ~1.2 gigawatts • OpenAI's planned campus: 10 gigawatts • Total cost: at least $500 billion if fully built out • All four hyperscalers combined are spending ~$700 billion this year • OpenAI has raised... show more

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

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

The Assembly

7,294,483 просмотров • 3 месяцев назад

$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

1,197,773 просмотров • 6 месяцев назад

OpenAI is building a $20 billion dollar project in GA, Residents just found out The project will consume 3.2 gigawatts of electricity, enough to power more than 2 million homes - almost half of all homes in Georgia. The project will use massive amounts of water in an area that is already facing shortages. At nearly $30 billion dollars total cost, this will be the most expensive project in Georgia's history. Open AI won't pay a dime in sales tax. No vote was held, the people of Georgia were not asked if they wanted this.

OpenAI is building a $20 billion dollar project in GA, Residents just found out The project will consume 3.2 gigawatts of electricity, enough to power more than 2 million homes - almost half of all homes in Georgia. The project will use massive amounts of water in an area that is already facing shortages. At nearly $30 billion dollars total cost, this will be the most expensive project in Georgia's history. Open AI won't pay a dime in sales tax. No vote was held, the people of Georgia were not asked if they wanted this.

Orwell Day

23,295 просмотров • 1 месяц назад

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 просмотров • 4 месяцев назад

Eric Schmidt says the real limit on AI is cash, and he puts one gigawatt of data center at roughly $50 billion: "A gigawatt data center costs something on the order of 50 billion with a B number." "How could these people in my industry be so crazy to raise all that money and build all the data centers? And the answer is they see the demand." "So absent an AI breakthrough algorithmically, which is a change to what is called the transformer architecture which is invented at Google, thank you, in 2017, we're sort of stuck with this cost structure." "And I think the real limit to AI is not energy. It's actually cash." "Because when you add up the cost of these, if you take 50, just round numbers, 50 billion a gigawatt, so 10 gigawatts is half a trillion dollars." "How many companies, countries, and so forth can hand an industry a trillion dollars of capital? Very, very few." Even at the low end of the published estimates, around $38 billion a gigawatt, his arithmetic still puts ten gigawatts in the hundreds of billions, so the conclusion holds. Very few balance sheets can carry that, which means most companies buying AI capacity over the next few years will be renting it from the handful that can. - Eric Schmidt (Eric Schmidt), Chair of the Special Competitive Studies Project and CEO of Relativity Space, at the SCSP AI+ Expo (@SCSPAI), May 2026.

Eric Schmidt says the real limit on AI is cash, and he puts one gigawatt of data center at roughly $50 billion: "A gigawatt data center costs something on the order of 50 billion with a B number." "How could these people in my industry be so crazy to raise all that money and build all the data centers? And the answer is they see the demand." "So absent an AI breakthrough algorithmically, which is a change to what is called the transformer architecture which is invented at Google, thank you, in 2017, we're sort of stuck with this cost structure." "And I think the real limit to AI is not energy. It's actually cash." "Because when you add up the cost of these, if you take 50, just round numbers, 50 billion a gigawatt, so 10 gigawatts is half a trillion dollars." "How many companies, countries, and so forth can hand an industry a trillion dollars of capital? Very, very few." Even at the low end of the published estimates, around $38 billion a gigawatt, his arithmetic still puts ten gigawatts in the hundreds of billions, so the conclusion holds. Very few balance sheets can carry that, which means most companies buying AI capacity over the next few years will be renting it from the handful that can. - Eric Schmidt (Eric Schmidt), Chair of the Special Competitive Studies Project and CEO of Relativity Space, at the SCSP AI+ Expo (@SCSPAI), May 2026.

Karl Mehta

39,848 просмотров • 6 дней назад

ABC News investigated and found more than 3,000 data centers are already operating nationwide At least 1,000 more planned Residents near data centers are seeing much as 50%+ increases on their electric bills “ABC7 has also been covering public meetings over proposed data centers and there are questions about water use and the environment. The i-team in ABC News studied this private company's data center map and found that there are at least 4,302 data center projects across the U.S. Large and small. Of those, 3,038 are currently operational with another 1,203 either under construction or plan for construction. 61 have acquired land. In Illinois, there are 164 operating data centers with another 81 planned for construction. The largest state project plan is in Yorkville. It would be 2 gigawatts and according to the ABC7 data team would use the same energy that would power approximately 1.7 million homes more than every home in the city of Chicago.”

ABC News investigated and found more than 3,000 data centers are already operating nationwide At least 1,000 more planned Residents near data centers are seeing much as 50%+ increases on their electric bills “ABC7 has also been covering public meetings over proposed data centers and there are questions about water use and the environment. The i-team in ABC News studied this private company's data center map and found that there are at least 4,302 data center projects across the U.S. Large and small. Of those, 3,038 are currently operational with another 1,203 either under construction or plan for construction. 61 have acquired land. In Illinois, there are 164 operating data centers with another 81 planned for construction. The largest state project plan is in Yorkville. It would be 2 gigawatts and according to the ABC7 data team would use the same energy that would power approximately 1.7 million homes more than every home in the city of Chicago.”

Wall Street Apes

152,195 просмотров • 6 месяцев назад

This is a before and after of the water level at Lake Powell Lake Powell’s water level today is at critically low levels. Some parts are completely dry and overall it’s only at 23% capacity 24 large hyperscale data centers and 379 smaller data centers are located across the 7 Colorado River Basin states Cities, farms and industry in 7 states and Mexico pull more water than The Colorado River reliably supplies To make things even worse, A high-profile proposed $10 billion data center is being planned right next to Lake Powell

Wall Street Apes

107,458 просмотров • 2 месяцев назад

There are RVs parked for miles in Abilene, Texas They are used for temporary housing for thousands of construction workers building massive AI data centers Abilene is in the middle of a huge AI data center boom, projects include OpenAI, Oracle, Crusoe, Microsoft, and more. These are multibillion dollar campuses, some valued at more than $26 billion+ The power needs for these data centers in this area will exceed 1 million average homes They’ll use about 8 million gallons of water

There are RVs parked for miles in Abilene, Texas They are used for temporary housing for thousands of construction workers building massive AI data centers Abilene is in the middle of a huge AI data center boom, projects include OpenAI, Oracle, Crusoe, Microsoft, and more. These are multibillion dollar campuses, some valued at more than $26 billion+ The power needs for these data centers in this area will exceed 1 million average homes They’ll use about 8 million gallons of water

Wall Street Apes

334,605 просмотров • 3 месяцев назад

New scenes from the Hazen Fire (Buckeye brush fire) burning south of Buckeye, Arizona The fire as of right now is still 0% contained and has burned nearly 1,000 acres Coincidentally Buckeye, Arizona has multiple large-scale data center projects planned Planned data centers nearby include - Tract Buckeye Technology Park is the largest and most prominent. A 2,069 acre campus for up to 20 million sq ft of data centers with 40 buildings - Hassayampa Ranch: Another massive 2,000 acre $25 billion data center project west in unincorporated Maricopa County - There are additional smaller data center proposals also, including conversions of industrial and hydrogen sites The fire seems to be clearing the land

New scenes from the Hazen Fire (Buckeye brush fire) burning south of Buckeye, Arizona The fire as of right now is still 0% contained and has burned nearly 1,000 acres Coincidentally Buckeye, Arizona has multiple large-scale data center projects planned Planned data centers nearby include - Tract Buckeye Technology Park is the largest and most prominent. A 2,069 acre campus for up to 20 million sq ft of data centers with 40 buildings - Hassayampa Ranch: Another massive 2,000 acre $25 billion data center project west in unincorporated Maricopa County - There are additional smaller data center proposals also, including conversions of industrial and hydrogen sites The fire seems to be clearing the land

Wall Street Apes

97,175 просмотров • 3 месяцев назад

.Dept. of Agriculture has NEVER had access to State SNAP data. Not until this Administration demanded it. That’s why every figure from years past is meaningless. From the 29 states that DID share data, we’ve already identified at least $3 billion a year in fraud. Extrapolated nationwide: more than $10 billion. This isn’t “erroneous payments.” This is FRAUD — and yes, Angie Craig, I know the difference. Do you?

.Dept. of Agriculture has NEVER had access to State SNAP data. Not until this Administration demanded it. That’s why every figure from years past is meaningless. From the 29 states that DID share data, we’ve already identified at least $3 billion a year in fraud. Extrapolated nationwide: more than $10 billion. This isn’t “erroneous payments.” This is FRAUD — and yes, Angie Craig, I know the difference. Do you?

Secretary Brooke Rollins

1,413,629 просмотров • 2 месяцев назад

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

159,345 просмотров • 3 месяцев назад

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 просмотров • 3 месяцев назад

SpaceX COO Gwynne Shotwell speaking about xAI's plans: • xAI will build 1.2 gigawatts of power for its supercomputer now and for all future data centers • Expanding the biggest Tesla Megapack system in the world — enough backup power for all of Memphis and more than Southaven needs (where the data center is) • New water recycling plants to save about 4.7 billion gallons of water each year from the Memphis aquifer • Thousands of new jobs mostly for people in Memphis, plus cheaper electricity for Americans • Plans to put supercomputers in space (orbit) to use huge amounts of energy more efficiently

SpaceX COO Gwynne Shotwell speaking about xAI's plans: • xAI will build 1.2 gigawatts of power for its supercomputer now and for all future data centers • Expanding the biggest Tesla Megapack system in the world — enough backup power for all of Memphis and more than Southaven needs (where the data center is) • New water recycling plants to save about 4.7 billion gallons of water each year from the Memphis aquifer • Thousands of new jobs mostly for people in Memphis, plus cheaper electricity for Americans • Plans to put supercomputers in space (orbit) to use huge amounts of energy more efficiently

Dima Zeniuk

434,185 просмотров • 5 месяцев назад

🚨 THIS IS EXTREMELY BAD FOR $NVDA. China is preparing a $295 billion plan to build AI data centers across the whole country. The catch for America: at least 80% of the chips must be homegrown. That means Huawei in. Nvidia out. Jensen Huang confirmed this last month. Nvidia has "largely conceded" China to Huawei, he told CNBC. China once accounted for at least 20% of Nvidia's entire data center revenue. That market is now all but GONE. America spent years locking China out. China just stopped knocking.

🚨 THIS IS EXTREMELY BAD FOR $NVDA. China is preparing a $295 billion plan to build AI data centers across the whole country. The catch for America: at least 80% of the chips must be homegrown. That means Huawei in. Nvidia out. Jensen Huang confirmed this last month. Nvidia has "largely conceded" China to Huawei, he told CNBC. China once accounted for at least 20% of Nvidia's entire data center revenue. That market is now all but GONE. America spent years locking China out. China just stopped knocking.

CryptoGoos

187,769 просмотров • 2 месяцев назад

Georgia is basically turning into one large data center Get ready for this, there is no legal obligation for data centers to disclose how much water they will be using - Georgia currently has about 162 data centers already - They have an additional 141 new data centers planned - Combined these data centers will use 12+ GW or more of power, this is equivalent to the usage of 10 MILLION homes - Combined water usage estimate of 35+ billion gallons per year or higher Absolutely insane There is no comprehensive federal requirement for data centers to publicly report detailed water usage. A bill was introduced called “the Data Center Water and Energy Transparency Act” to mandate reporting of energy and water consumption to states and the EPA This is an issue, here’s one example The Quality Technology Services data center in Fayette County used 29–30 million gallons of water went unmetered and unbilled for months without initial detection. Residents complained about low pressure during drought conditions. The company later paid retroactively $150,000 but faced no fines

Georgia is basically turning into one large data center Get ready for this, there is no legal obligation for data centers to disclose how much water they will be using - Georgia currently has about 162 data centers already - They have an additional 141 new data centers planned - Combined these data centers will use 12+ GW or more of power, this is equivalent to the usage of 10 MILLION homes - Combined water usage estimate of 35+ billion gallons per year or higher Absolutely insane There is no comprehensive federal requirement for data centers to publicly report detailed water usage. A bill was introduced called “the Data Center Water and Energy Transparency Act” to mandate reporting of energy and water consumption to states and the EPA This is an issue, here’s one example The Quality Technology Services data center in Fayette County used 29–30 million gallons of water went unmetered and unbilled for months without initial detection. Residents complained about low pressure during drought conditions. The company later paid retroactively $150,000 but faced no fines

Wall Street Apes

147,658 просмотров • 3 месяцев назад

A new HUGE data center campus called Project Open Sky is being planned in Oklahoma. The land will be over a square mile with 6 Data Centers One American family all built houses together on a compound, and the data center campus is planned less than 300 feet away from their homes The residents say they already have a water pressure issue and this is going to mean there won’t be enough water to farm or even for their homes The data center campus could use as 27.4 million gallons per year “They literally have an entire square mile and are pushing to get more — Cloverleaf Infrastructure is the company behind Project Open Sky, which is in talks to build a 633-acre campus with as many as 6 data centers on it” This is going to destroy the lives of the residents in this town

A new HUGE data center campus called Project Open Sky is being planned in Oklahoma. The land will be over a square mile with 6 Data Centers One American family all built houses together on a compound, and the data center campus is planned less than 300 feet away from their homes The residents say they already have a water pressure issue and this is going to mean there won’t be enough water to farm or even for their homes The data center campus could use as 27.4 million gallons per year “They literally have an entire square mile and are pushing to get more — Cloverleaf Infrastructure is the company behind Project Open Sky, which is in talks to build a 633-acre campus with as many as 6 data centers on it” This is going to destroy the lives of the residents in this town

Wall Street Apes

55,820 просмотров • 1 день назад

AI INFRASTRUCTURE/ENERGY DEMAND STOCKS TO KEEP ON WATCH FOR 2026 Ex-CEO $GOOGL Eric Schmidt on energy demand driven by AI: "We need energy and the numbers are profound. What we need from you is energy in all forms. People are planning 10 gigawatt data centers" $IREN: owns and develops vertically integrated data centers for hyperscalers $CIFR: large power footprint, 3.4 GW pipeline for AI workloads + HPC $WULF: high capacity, low cost data center expansion across Texas and New York $NBIS: AI compute and cloud services translating energy into revenue $CLSK: America’s Bitcoin Miner transitioning to AI infrastructure with a massive power footprint across 30+ data center sites $BITF: owns and operates power sites positioned for AI workloads, yet to sign with a hyperscaler but could come this year $GLXY: multi-gigawatt data center infrastructure at scale

AI INFRASTRUCTURE/ENERGY DEMAND STOCKS TO KEEP ON WATCH FOR 2026 Ex-CEO $GOOGL Eric Schmidt on energy demand driven by AI: "We need energy and the numbers are profound. What we need from you is energy in all forms. People are planning 10 gigawatt data centers" $IREN: owns and develops vertically integrated data centers for hyperscalers $CIFR: large power footprint, 3.4 GW pipeline for AI workloads + HPC $WULF: high capacity, low cost data center expansion across Texas and New York $NBIS: AI compute and cloud services translating energy into revenue $CLSK: America’s Bitcoin Miner transitioning to AI infrastructure with a massive power footprint across 30+ data center sites $BITF: owns and operates power sites positioned for AI workloads, yet to sign with a hyperscaler but could come this year $GLXY: multi-gigawatt data center infrastructure at scale

Small Cap Snipa

116,034 просмотров • 7 месяцев назад

Elon Musk announced a chip factory 10 times the size of Tesla's Gigafactory. The goal is to produce enough AI compute to equal twice the entire electricity consumption of the United States. He called it the Terafab. Here is the number that stopped me cold. The entire global AI chip industry right now is on track to hit around 100 gigawatts per year of compute. Every Nvidia GPU, every Google TPU, every chip from every company on earth combined. 100 gigawatts. Musk wants one factory to produce a terawatt per year. A terawatt is 1,000 gigawatts. Ten times the output of the entire global industry. From a single building. To put the scale in physical terms, the Terafab would need to be around 100 million square feet. You would need Starship point to point transport just to get from one end to the other. But the reason for the scale is not ambition for its own sake. To launch meaningful AI compute into space, you need a billion chips per year running at a kilowatt each. That is not a number the current industry can produce. The Terafab is the only way to get there. The timeline he put out: a gigawatt of space AI compute annualized by end of next year. Then 10x per year from there. 10 gigawatts by year two. 100 gigawatts by year three. A terawatt beyond that. Most people think orbital data centers are a decade away. Musk is building the factory to make them possible by next year.

Elon Musk announced a chip factory 10 times the size of Tesla's Gigafactory. The goal is to produce enough AI compute to equal twice the entire electricity consumption of the United States. He called it the Terafab. Here is the number that stopped me cold. The entire global AI chip industry right now is on track to hit around 100 gigawatts per year of compute. Every Nvidia GPU, every Google TPU, every chip from every company on earth combined. 100 gigawatts. Musk wants one factory to produce a terawatt per year. A terawatt is 1,000 gigawatts. Ten times the output of the entire global industry. From a single building. To put the scale in physical terms, the Terafab would need to be around 100 million square feet. You would need Starship point to point transport just to get from one end to the other. But the reason for the scale is not ambition for its own sake. To launch meaningful AI compute into space, you need a billion chips per year running at a kilowatt each. That is not a number the current industry can produce. The Terafab is the only way to get there. The timeline he put out: a gigawatt of space AI compute annualized by end of next year. Then 10x per year from there. 10 gigawatts by year two. 100 gigawatts by year three. A terawatt beyond that. Most people think orbital data centers are a decade away. Musk is building the factory to make them possible by next year.

Ihtesham Ali

318,363 просмотров • 2 месяцев назад

Today I sat down with John McQueeney, State Representative for House District 97 in Tarrant County, Texas and member of the State Affairs Committee covering power grid and electric policy. In the last six weeks alone, John's committee has run three interim data center hearings. He is also drafting the Data Center Responsibility Act for the January 2027 session - the bill that will set the framework for how Texas handles the data center build-out for a generation. Texas has 440 gigawatts of applications in the queue against roughly 110 gigawatts of current peak capacity. Someone has to sort out what's real, what's speculative, and who pays for the grid when it all comes online. John is one of the people doing that work. I hope you enjoy this episode as much as I did. Timestamps (0:00) Intro (02:27) Why Data Centers Are a "12 Out of 10" for Texas (08:17) A Day Without a Data Center (09:34) Inside Stargate: Lancium, Crusoe, Oracle & OpenAI (14:34) When One Data Center Funds 30% of a City's Budget (17:03) The Vicious Restudy Cycle & the Batch Zero Fix (28:55) 440 GW of Applications Chasing 105 GW of Capacity (35:53) The 75 MW Threshold & Going Behind the Meter (48:36) Drafting the Data Center Responsibility Act (54:19) North Texas's Hidden Risk in Batch Zero (01:08:35) Who Actually Pays for the Grid Buildout? (01:14:32) Data Centers Are a National Security Issue (01:18:12) Data Centers in Space & the Long Arc

Today I sat down with John McQueeney, State Representative for House District 97 in Tarrant County, Texas and member of the State Affairs Committee covering power grid and electric policy. In the last six weeks alone, John's committee has run three interim data center hearings. He is also drafting the Data Center Responsibility Act for the January 2027 session - the bill that will set the framework for how Texas handles the data center build-out for a generation. Texas has 440 gigawatts of applications in the queue against roughly 110 gigawatts of current peak capacity. Someone has to sort out what's real, what's speculative, and who pays for the grid when it all comes online. John is one of the people doing that work. I hope you enjoy this episode as much as I did. Timestamps (0:00) Intro (02:27) Why Data Centers Are a "12 Out of 10" for Texas (08:17) A Day Without a Data Center (09:34) Inside Stargate: Lancium, Crusoe, Oracle & OpenAI (14:34) When One Data Center Funds 30% of a City's Budget (17:03) The Vicious Restudy Cycle & the Batch Zero Fix (28:55) 440 GW of Applications Chasing 105 GW of Capacity (35:53) The 75 MW Threshold & Going Behind the Meter (48:36) Drafting the Data Center Responsibility Act (54:19) North Texas's Hidden Risk in Batch Zero (01:08:35) Who Actually Pays for the Grid Buildout? (01:14:32) Data Centers Are a National Security Issue (01:18:12) Data Centers in Space & the Long Arc

Chris Powers

15,875 просмотров • 3 месяцев назад

Elon Musk just confirmed the most INSANE IPO in history. SpaceX is going public in 2026. $1.5 TRILLION valuation. Raising $30+ billion. That's the biggest IPO ever made. Beating Saudi Aramco's $29 billion record from 2019. But here's what everyone's missing: This isn't about space tourism or Mars missions. Elon is literally about to win the entire AI race. And 99% of people have no idea how... Here's the problem killing every AI company right now: POWER. Oracle just reported earnings. They burned through $12 BILLION in one quarter building data centers. Their free cash flow? NEGATIVE $10 billion. Revenue missed estimates. Stock crashed 11%. Microsoft, Amazon, Google all scrambling to find enough electricity for AI training. The brutal math: The US generates 490 gigawatts of total power. AI is projected to need 123 gigawatts by 2035. That's a QUARTER of the entire electrical grid. Just for artificial intelligence. Goldman Sachs says AI energy demand could jump 165% by 2030. There is literally not enough power on Earth to run AI at the scale these companies are promising. Every data center needs massive cooling systems. Billions of gallons of water per year. Insane energy costs. And the infrastructure can't keep up. Elon's solution? Stop building on Earth entirely. SpaceX is building data centers in SPACE. Not a concept. Not 10 years out. Literally starting in 2026. They're upgrading Starlink V3 satellites to carry AI computing chips. Each satellite gets 24/7 solar power. No clouds. No night. No weather disruptions. No grid bottlenecks. And the insane part is that Starship can deliver 300 to 500 gigawatts of solar-powered AI satellites into orbit every single year. At 300 gigawatts per year, the AI computing power in space would exceed the entire U.S. economy's total electricity consumption within two years. Just from satellites. Processing in orbit. While Oracle is begging banks for loans to finish data centers and OpenAI is stuck in circular funding arrangements with Microsoft, Elon already owns everything: The rockets. The satellites. The launch infrastructure. The AI company (xAI). He doesn't need to ask utilities for permission. Doesn't need grid approvals from local governments. Doesn't need to build nuclear plants or wait for clean energy. He just launches. And everyone else is scrambling to catch up: Jeff Bezos sees it. Blue Origin announced they're building their own orbital data centers. Google just launched "Project Suncatcher" with plans to deploy AI satellites by 2027. Eric Schmidt, the former CEO of Google, literally BOUGHT an entire rocket company (Relativity Space) just to compete in this space. But they're all 3+ years behind Elon. SpaceX already has 6,000+ Starlink satellites in orbit. The infrastructure is built. The $30 billion from the IPO? Going straight into scaling orbital compute. SpaceX revenue is jumping from $15 billion in 2025 to $24 billion in 2026. Most of that from Starlink. Now add space-based AI infrastructure on top. Here's why this matters: Whoever controls orbital computing controls the AI revolution. And there's only ONE company on Earth with fully reusable rockets that can launch at the scale required. Jensen Huang, Nvidia's CEO, called space data centers "a dream." Translation: Nvidia is screwed if Elon actually pulls this off. Because if SpaceX succeeds, every AI company on the planet becomes Elon's customer. OpenAI needs compute? Running on SpaceX satellites. Google needs more capacity? Renting orbital infrastructure. Microsoft needs power? Paying SpaceX for launch and compute access. Elon won't just be in the AI race. He'll own the entire track everyone else is running on. The $1.5 trillion valuation sounds crazy until you realize what he's actually building. It's not a rocket company. It's the infrastructure layer for the next 50 years of computing. People calling it overvalued have no idea what's coming.

Elon Musk just confirmed the most INSANE IPO in history. SpaceX is going public in 2026. $1.5 TRILLION valuation. Raising $30+ billion. That's the biggest IPO ever made. Beating Saudi Aramco's $29 billion record from 2019. But here's what everyone's missing: This isn't about space tourism or Mars missions. Elon is literally about to win the entire AI race. And 99% of people have no idea how... Here's the problem killing every AI company right now: POWER. Oracle just reported earnings. They burned through $12 BILLION in one quarter building data centers. Their free cash flow? NEGATIVE $10 billion. Revenue missed estimates. Stock crashed 11%. Microsoft, Amazon, Google all scrambling to find enough electricity for AI training. The brutal math: The US generates 490 gigawatts of total power. AI is projected to need 123 gigawatts by 2035. That's a QUARTER of the entire electrical grid. Just for artificial intelligence. Goldman Sachs says AI energy demand could jump 165% by 2030. There is literally not enough power on Earth to run AI at the scale these companies are promising. Every data center needs massive cooling systems. Billions of gallons of water per year. Insane energy costs. And the infrastructure can't keep up. Elon's solution? Stop building on Earth entirely. SpaceX is building data centers in SPACE. Not a concept. Not 10 years out. Literally starting in 2026. They're upgrading Starlink V3 satellites to carry AI computing chips. Each satellite gets 24/7 solar power. No clouds. No night. No weather disruptions. No grid bottlenecks. And the insane part is that Starship can deliver 300 to 500 gigawatts of solar-powered AI satellites into orbit every single year. At 300 gigawatts per year, the AI computing power in space would exceed the entire U.S. economy's total electricity consumption within two years. Just from satellites. Processing in orbit. While Oracle is begging banks for loans to finish data centers and OpenAI is stuck in circular funding arrangements with Microsoft, Elon already owns everything: The rockets. The satellites. The launch infrastructure. The AI company (xAI). He doesn't need to ask utilities for permission. Doesn't need grid approvals from local governments. Doesn't need to build nuclear plants or wait for clean energy. He just launches. And everyone else is scrambling to catch up: Jeff Bezos sees it. Blue Origin announced they're building their own orbital data centers. Google just launched "Project Suncatcher" with plans to deploy AI satellites by 2027. Eric Schmidt, the former CEO of Google, literally BOUGHT an entire rocket company (Relativity Space) just to compete in this space. But they're all 3+ years behind Elon. SpaceX already has 6,000+ Starlink satellites in orbit. The infrastructure is built. The $30 billion from the IPO? Going straight into scaling orbital compute. SpaceX revenue is jumping from $15 billion in 2025 to $24 billion in 2026. Most of that from Starlink. Now add space-based AI infrastructure on top. Here's why this matters: Whoever controls orbital computing controls the AI revolution. And there's only ONE company on Earth with fully reusable rockets that can launch at the scale required. Jensen Huang, Nvidia's CEO, called space data centers "a dream." Translation: Nvidia is screwed if Elon actually pulls this off. Because if SpaceX succeeds, every AI company on the planet becomes Elon's customer. OpenAI needs compute? Running on SpaceX satellites. Google needs more capacity? Renting orbital infrastructure. Microsoft needs power? Paying SpaceX for launch and compute access. Elon won't just be in the AI race. He'll own the entire track everyone else is running on. The $1.5 trillion valuation sounds crazy until you realize what he's actually building. It's not a rocket company. It's the infrastructure layer for the next 50 years of computing. People calling it overvalued have no idea what's coming.

Ricardo

2,908,788 просмотров • 8 месяцев назад