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Is DeepMind taking over Google? Demis Hassabis just stepped down as CEO of Google DeepMind, moved to chairman, and teased unreleased Gemini 4 by name. OpenAI's Astra solved 10 decades-old math problems for $2,000 and SpaceX laid out a path to the first trillion-dollar revenue year in history. --...

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Peter H. Diamandis, MD

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41,001 просмотров • 9 дней назад •via X (Twitter)

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🚀 Ron Baron now has roughly $25 billion invested in SpaceX, making it the largest position across his funds. After speaking with Elon Musk, Baron says Musk believes SpaceX is still "just getting started." The long-term vision is enormous: Starlink, reusable rockets, AI infrastructure, compute, chips, and a global communications network that few competitors can match. Ron Baron believes SpaceX is years ahead in several key industries and expects the investment to generate hundreds of billions of dollars over time. The most interesting part? SpaceX generated about $19 billion in revenue last year, yet some projections see a path toward $1 trillion in annual revenue by 2030! That's the kind of scale investors are trying to wrap their heads around. 👀 $SPCX
5:34

🚀 Ron Baron now has roughly $25 billion invested in SpaceX, making it the largest position across his funds. After speaking with Elon Musk, Baron says Musk believes SpaceX is still "just getting started." The long-term vision is enormous: Starlink, reusable rockets, AI infrastructure, compute, chips, and a global communications network that few competitors can match. Ron Baron believes SpaceX is years ahead in several key industries and expects the investment to generate hundreds of billions of dollars over time. The most interesting part? SpaceX generated about $19 billion in revenue last year, yet some projections see a path toward $1 trillion in annual revenue by 2030! That's the kind of scale investors are trying to wrap their heads around. 👀 $SPCX

Herbert Ong

8,770,548 просмотров • 2 месяцев назад

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!
4:04

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 просмотров • 2 месяцев назад

A historic day for financial markets as SpaceX achieves the largest IPO in history at $1.75T The numbers are big but I believe we are early in SpaceX’s arc to make humans multi planetary and become larger than the combined GDP of the world today ($100T ish) Both Starlink and AI satellites can be multi trillion dollar business and are the first two applications of having the reusable rocket launch Next will be building infrastructure on the moon, mars and then asteroid mining Revenue was at $18.8B as of Q1 26 but has already doubled since with the Anthropic and Google deals. Combined with Cursor and Starlink V3 ramp later this year we will be approaching a $50B revenue run rate in just a few months By 2030 I project $500B in potential revenue with half of that if not more as operating cashflow At a 20x multiple on 50% margins we hit $5T valuation in just 3.5 years … and rapidly growing intrinsic value from there Spacex could easily not focus on revenue this much and continue to just build its core tech for moon and mars , we’ll see Either way, incredibly pumped to be a $SPCX shareholder and congrats to all employees and Elon Musk in this epic IPO. To the moon and mars !!!!! 🚀🚀🚀
36:17

A historic day for financial markets as SpaceX achieves the largest IPO in history at $1.75T The numbers are big but I believe we are early in SpaceX’s arc to make humans multi planetary and become larger than the combined GDP of the world today ($100T ish) Both Starlink and AI satellites can be multi trillion dollar business and are the first two applications of having the reusable rocket launch Next will be building infrastructure on the moon, mars and then asteroid mining Revenue was at $18.8B as of Q1 26 but has already doubled since with the Anthropic and Google deals. Combined with Cursor and Starlink V3 ramp later this year we will be approaching a $50B revenue run rate in just a few months By 2030 I project $500B in potential revenue with half of that if not more as operating cashflow At a 20x multiple on 50% margins we hit $5T valuation in just 3.5 years … and rapidly growing intrinsic value from there Spacex could easily not focus on revenue this much and continue to just build its core tech for moon and mars , we’ll see Either way, incredibly pumped to be a $SPCX shareholder and congrats to all employees and Elon Musk in this epic IPO. To the moon and mars !!!!! 🚀🚀🚀

Gali

16,958 просмотров • 2 месяцев назад

The CEO of Anthropic just said we are 1 to 3 years away from AGI. On camera. With 90% confidence. Almost nobody watched it. INSTEAD OF ARGUING ABOUT AI TAKING JOBS. Spend 2 hours watching the CEO of Anthropic explain exactly when and how it happens. The AI compute arms race just got a reality check nobody expected. Dario Amodei, CEO of Anthropic just did the math out loud: → Revenue growing 10x per year means $100B by end of 2026 and $1T by end of 2027 → At that trajectory you could theoretically buy $5T in compute over 5 years → But if revenue comes in at even $800B instead of $1T, bankruptcy. No exceptions → And if growth slows from 10x to just 5x per year, the entire model collapses by one year This is the most honest thing anyone in AI has said publicly in years. The companies building AI infrastructure are making trillion-dollar bets on growth curves that have never existed before in history. One year off. One multiplier wrong. The whole thing unravels. The AI compute boom is real. The risk underneath it is equally real. The question is not whether AI is the future. It is whether anyone can survive long enough to get there
2:22:19

The CEO of Anthropic just said we are 1 to 3 years away from AGI. On camera. With 90% confidence. Almost nobody watched it. INSTEAD OF ARGUING ABOUT AI TAKING JOBS. Spend 2 hours watching the CEO of Anthropic explain exactly when and how it happens. The AI compute arms race just got a reality check nobody expected. Dario Amodei, CEO of Anthropic just did the math out loud: → Revenue growing 10x per year means $100B by end of 2026 and $1T by end of 2027 → At that trajectory you could theoretically buy $5T in compute over 5 years → But if revenue comes in at even $800B instead of $1T, bankruptcy. No exceptions → And if growth slows from 10x to just 5x per year, the entire model collapses by one year This is the most honest thing anyone in AI has said publicly in years. The companies building AI infrastructure are making trillion-dollar bets on growth curves that have never existed before in history. One year off. One multiplier wrong. The whole thing unravels. The AI compute boom is real. The risk underneath it is equally real. The question is not whether AI is the future. It is whether anyone can survive long enough to get there

Dami-Defi

16,080 просмотров • 3 месяцев назад

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.
2:08

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 просмотров • 2 месяцев назад

Peter Diamandis: SpaceX has the potential to become the world’s first $10 trillion company “Well, if anybody can do it, Elon can. I think this has the potential to really be the first $10 trillion company out there and growing. He’s building civilizational-level infrastructure. The challenge is, I don’t think the market knows how to value this company. It’s not a company, it’s really four different businesses wrapped into one vertical, and you have to look at each individually. “The first business is global communications with Starlink. Starlink is going to deliver global gigabit connectivity to the entire planet, billions of individuals. They’re just making a dent right now. Then they’re going direct satellite-to-cell phone. As Gwynne said on the earnings call yesterday, that’s a $600 billion level of revenue potential, and they expect to take a chunk of that. “The second business is delivering AI compute. They’ve already signed up $20 billion in annualized revenue, and they’re building faster than anybody else. They announced two gigawatts of compute by the end of this year and are shooting for upwards of 10 gigawatts next year… Elon said they’re launching their first AI satellites in partnership with Nvidia in 2027, much faster than anybody thought.”
2:32

Peter Diamandis: SpaceX has the potential to become the world’s first $10 trillion company “Well, if anybody can do it, Elon can. I think this has the potential to really be the first $10 trillion company out there and growing. He’s building civilizational-level infrastructure. The challenge is, I don’t think the market knows how to value this company. It’s not a company, it’s really four different businesses wrapped into one vertical, and you have to look at each individually. “The first business is global communications with Starlink. Starlink is going to deliver global gigabit connectivity to the entire planet, billions of individuals. They’re just making a dent right now. Then they’re going direct satellite-to-cell phone. As Gwynne said on the earnings call yesterday, that’s a $600 billion level of revenue potential, and they expect to take a chunk of that. “The second business is delivering AI compute. They’ve already signed up $20 billion in annualized revenue, and they’re building faster than anybody else. They announced two gigawatts of compute by the end of this year and are shooting for upwards of 10 gigawatts next year… Elon said they’re launching their first AI satellites in partnership with Nvidia in 2027, much faster than anybody thought.”

DogeDesigner

47,675 просмотров • 14 дней назад

I had a chance to sit down with Demis Hassabis to discuss his goal of solving intelligence and using it to help cure all disease. But what I found most compelling wasn't the scale of the mission, but Demis Hassabis himself. His level of focus is extraordinary. We talked about the personal cost of pursuing a mission this ambitious, and the tension between the two sides of his work: the CEO of a commercial entity and the scientist driven by a humanitarian vision. It was an absolutely fascinating conversation, and a deep honor to speak with one of the most important minds of our time. Thank you to the Google DeepMind team for having me. (0:00) Curing Every Disease in a Decade (1:04) Gemini for Science (2:01) Changing Science Forever with AlphaFold (4:04) Can Humans Trust AI In The Medical Field? (6:02) Generative AI vs. Practical AI (7:03) The Tension Between CEO & Scientist (8:28) AGI by 2030 (10:07) The Chess Prodigy Turned CEO (11:20) Ender's Game & What This Mission Has Cost
13:44

I had a chance to sit down with Demis Hassabis to discuss his goal of solving intelligence and using it to help cure all disease. But what I found most compelling wasn't the scale of the mission, but Demis Hassabis himself. His level of focus is extraordinary. We talked about the personal cost of pursuing a mission this ambitious, and the tension between the two sides of his work: the CEO of a commercial entity and the scientist driven by a humanitarian vision. It was an absolutely fascinating conversation, and a deep honor to speak with one of the most important minds of our time. Thank you to the Google DeepMind team for having me. (0:00) Curing Every Disease in a Decade (1:04) Gemini for Science (2:01) Changing Science Forever with AlphaFold (4:04) Can Humans Trust AI In The Medical Field? (6:02) Generative AI vs. Practical AI (7:03) The Tension Between CEO & Scientist (8:28) AGI by 2030 (10:07) The Chess Prodigy Turned CEO (11:20) Ender's Game & What This Mission Has Cost

Roberto Nickson

51,426 просмотров • 2 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.
0:22

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 • 2 месяцев назад

I think Starlink is wildly undervalued. It’s a $1+ trillion company in the making on its own. A lot of people still think Starlink is just “internet from space,” but in reality, it’s one of the most important communications networks ever built. In 2025 alone, Starlink generated $11.4 billion in revenue, accounting for roughly 61% of SpaceX’s total revenue. It served more than 10 million customers globally and generated $4.4 billion in operating profit w/ EBITDA margins of 63%. Starlink is a cash machine. Fyi, independent analysts forecast Starlink will generate approximately $20 billion in revenue, $14 billion in EBITDA, and over $8 billion in free cash flow in 2026… plus consumer broadband will continue to expand rapidly, while aviation, maritime, Starshield, and direct-to-cell services will open entirely new markets. The real advantage is that Starlink owns the entire stack. SpaceX builds the satellites, they launch the satellites, they operate the network, and they manufacture the user terminals. No competitor comes close to that level of vertical integration…. On top of this, starship will make the story even more crazier with next-generation satellites, 100+ satellites per launch, dramatically lowering launch costs, and thousands of new satellites being deployed each year, the cost of serving additional customers continuing to fall, while the network & tech keep getting stronger. If you really want to understand why SpaceX is at a $2T valuation… start with Starlink. Starlink already generates the majority of SpaceX’s revenue, profit, and free cash flow. It helps fund Starship development, supports expansion across the company, and provides the financial engine behind SpaceX’s long-term ambitions. The bull case is based on real revenue, real profits, real customers, and a moat that gets wider every year… NOT hype. The way I see it, Starlink will become the most valuable communication company in human history and a $1 trillion valuation doesn’t sound crazy to me for this business/technology alone.
0:23

I think Starlink is wildly undervalued. It’s a $1+ trillion company in the making on its own. A lot of people still think Starlink is just “internet from space,” but in reality, it’s one of the most important communications networks ever built. In 2025 alone, Starlink generated $11.4 billion in revenue, accounting for roughly 61% of SpaceX’s total revenue. It served more than 10 million customers globally and generated $4.4 billion in operating profit w/ EBITDA margins of 63%. Starlink is a cash machine. Fyi, independent analysts forecast Starlink will generate approximately $20 billion in revenue, $14 billion in EBITDA, and over $8 billion in free cash flow in 2026… plus consumer broadband will continue to expand rapidly, while aviation, maritime, Starshield, and direct-to-cell services will open entirely new markets. The real advantage is that Starlink owns the entire stack. SpaceX builds the satellites, they launch the satellites, they operate the network, and they manufacture the user terminals. No competitor comes close to that level of vertical integration…. On top of this, starship will make the story even more crazier with next-generation satellites, 100+ satellites per launch, dramatically lowering launch costs, and thousands of new satellites being deployed each year, the cost of serving additional customers continuing to fall, while the network & tech keep getting stronger. If you really want to understand why SpaceX is at a $2T valuation… start with Starlink. Starlink already generates the majority of SpaceX’s revenue, profit, and free cash flow. It helps fund Starship development, supports expansion across the company, and provides the financial engine behind SpaceX’s long-term ambitions. The bull case is based on real revenue, real profits, real customers, and a moat that gets wider every year… NOT hype. The way I see it, Starlink will become the most valuable communication company in human history and a $1 trillion valuation doesn’t sound crazy to me for this business/technology alone.

Teslaconomics

28,276 просмотров • 2 месяцев назад

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.
2:03

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

208,495 просмотров • 3 месяцев назад

Chamath has been watching SpaceX for 15 years and he thinks the market is still not close to understanding what it actually is (Save this). The first argument is the industrial logic of a Tesla SpaceX combination. One capital structure, one balance sheet, one vehicle to raise money across robotics, autonomous vehicles, energy, AI, and launch. Chamath Palihapitiya argument is that markets are treating this as a peripheral possibility rather than an obvious strategic inevitability. The second is Starlink Direct to Cell, which he believes will generate enormous domestic cellular revenue before most of the bigger SpaceX narratives even begin to materialize. The numbers already back this up. Starlink has over 10 million Direct to Cell monthly active users with live partnerships with T-Mobile, Rogers and Optus standard smartphones connecting directly to satellites with no special hardware required. SpaceX is currently deploying approximately 340 Direct to Cell satellites per month, targeting 25 million monthly active users by end of 2026. Goldman forecasts SpaceX's AI division will generate $15.6 billion in 2026, rising to $34.5 billion in 2027 and accelerating to $322 billion by 2030 roughly a 100-fold increase in five years. Total SpaceX revenue hits $474 billion by 2030, up from $18.7 billion in 2025. The launch cadence numbers are where this gets staggering. SpaceX is expected to execute 151 Starship launches in 2027, scaling to 253 in 2028, then 1,504 in 2029, 2,808 in 2030, and 5,467 in 2031. Goldman projects 5,288 of those 2031 launches will be dedicated Starship AI missions each carrying 30 to 50 satellites powered by one GB300 equivalent compute rack apiece. The cost per kilogram to orbit falls below $100 as reusability matures, compared to $1,500 per kilogram on Falcon 9 today. Morgan Stanley projected a 24-hour turnaround by late 2027, enabling the kind of cadence these numbers require. That launch cost collapse is what makes the orbital AI compute thesis real Elon Musk
1:08

Chamath has been watching SpaceX for 15 years and he thinks the market is still not close to understanding what it actually is (Save this). The first argument is the industrial logic of a Tesla SpaceX combination. One capital structure, one balance sheet, one vehicle to raise money across robotics, autonomous vehicles, energy, AI, and launch. Chamath Palihapitiya argument is that markets are treating this as a peripheral possibility rather than an obvious strategic inevitability. The second is Starlink Direct to Cell, which he believes will generate enormous domestic cellular revenue before most of the bigger SpaceX narratives even begin to materialize. The numbers already back this up. Starlink has over 10 million Direct to Cell monthly active users with live partnerships with T-Mobile, Rogers and Optus standard smartphones connecting directly to satellites with no special hardware required. SpaceX is currently deploying approximately 340 Direct to Cell satellites per month, targeting 25 million monthly active users by end of 2026. Goldman forecasts SpaceX's AI division will generate $15.6 billion in 2026, rising to $34.5 billion in 2027 and accelerating to $322 billion by 2030 roughly a 100-fold increase in five years. Total SpaceX revenue hits $474 billion by 2030, up from $18.7 billion in 2025. The launch cadence numbers are where this gets staggering. SpaceX is expected to execute 151 Starship launches in 2027, scaling to 253 in 2028, then 1,504 in 2029, 2,808 in 2030, and 5,467 in 2031. Goldman projects 5,288 of those 2031 launches will be dedicated Starship AI missions each carrying 30 to 50 satellites powered by one GB300 equivalent compute rack apiece. The cost per kilogram to orbit falls below $100 as reusability matures, compared to $1,500 per kilogram on Falcon 9 today. Morgan Stanley projected a 24-hour turnaround by late 2027, enabling the kind of cadence these numbers require. That launch cost collapse is what makes the orbital AI compute thesis real Elon Musk

Milk Road AI

96,048 просмотров • 1 месяц назад

Elon just created the most valuable private company in history. And the VISION behind this move is going to win him the AI race. Yesterday, SpaceX and xAI combined in a $1.25 TRILLION deal, But this isn’t just a merger. Elon is literally solving AI’s biggest bottleneck: AI needs INSANE amounts of electricity. Every major AI company is hitting the same wall: Power constraints. OpenAI, Google, Anthropic are all racing to build bigger data centers. But they're all stuck on Earth fighting for the same limited power grid. Elon's solution: Move the data centers to SPACE. Last Friday, SpaceX filed with the FCC to launch up to 1 MILLION satellites. Not for internet. For compute. Solar-powered AI data centers in orbit that run 24/7 with zero cooling costs and unlimited energy from the sun. Look: On Earth, you need massive power plants, cooling systems, and infrastructure that costs billions and takes years to build. But in space? You have direct solar power. No cooling needed. Near-constant sunlight. According to Elon: "Within 2-3 years, space will be the lowest-cost way to generate AI compute." The numbers behind this are crazy: SpaceX made $8 billion profit on $15 billion revenue in 2025. xAI was valued at $230 billion standalone. Combined entity: $1.25 trillion heading into what could be the biggest IPO in history. And here's why this actually makes sense: SpaceX already dominates launches. 80% of their revenue comes from launching Starlink satellites. They've perfected reusable rockets. Launch costs keep dropping. Now instead of just launching communication satellites, they're launching compute infrastructure. xAI gets unlimited scalable compute without fighting for power grid access. SpaceX gets a customer that will need constant satellite refreshes and launches for decades. The vertical integration is incredible: SpaceX builds and launches the satellites. xAI runs the AI models on them. Grok gets trained on infrastructure no competitor can access. Starlink provides the communication backbone. Nobody else can replicate this. OpenAI can't launch rockets. Google can't either. What you have to understand about the upcoming IPO: This isn't just "rocket company goes public." It's "AI infrastructure company that happens to own the launch capability" goes public. Investors get exposure to both the AI race AND space commercialization in one ticker. That's why the $1.25 trillion valuation makes sense to Wall Street. Now here's the rational take: This is extremely ambitious. Maybe too ambitious. xAI is burning $1 billion per month right now competing with OpenAI. Space-based data centers have never been done at scale. The satellite constellation would be the largest in history by 100X. Technical challenges are massive. Regulatory approval isn't guaranteed. But if it works? Elon isn't just winning the AI race. He's changing WHERE the race happens. Imagine training AI models with 10X the compute power at 1/10th the cost because you're not constrained by Earth's power grid. That's game over for competition. The timeline to watch: Mid-2026: SpaceX/xAI IPO (largest in history) Late 2026: First orbital compute satellites launch 2027-2028: Proof of concept for space-based AI training If this actually delivers, we're looking at: The first trillion-dollar private company IPO. A new category of infrastructure (orbital compute). AI development unconstrained by terrestrial power limits. If it doesn't deliver? Well, it's still SpaceX with $8B in annual profit and dominance in launch services. Plus xAI with a $230B valuation and Grok. The risk-reward here is asymmetric. Downside: You own the world's most valuable rocket company. Upside: You own the infrastructure layer for all future AI development. Do you think datacenters in space could work?
1:29

Elon just created the most valuable private company in history. And the VISION behind this move is going to win him the AI race. Yesterday, SpaceX and xAI combined in a $1.25 TRILLION deal, But this isn’t just a merger. Elon is literally solving AI’s biggest bottleneck: AI needs INSANE amounts of electricity. Every major AI company is hitting the same wall: Power constraints. OpenAI, Google, Anthropic are all racing to build bigger data centers. But they're all stuck on Earth fighting for the same limited power grid. Elon's solution: Move the data centers to SPACE. Last Friday, SpaceX filed with the FCC to launch up to 1 MILLION satellites. Not for internet. For compute. Solar-powered AI data centers in orbit that run 24/7 with zero cooling costs and unlimited energy from the sun. Look: On Earth, you need massive power plants, cooling systems, and infrastructure that costs billions and takes years to build. But in space? You have direct solar power. No cooling needed. Near-constant sunlight. According to Elon: "Within 2-3 years, space will be the lowest-cost way to generate AI compute." The numbers behind this are crazy: SpaceX made $8 billion profit on $15 billion revenue in 2025. xAI was valued at $230 billion standalone. Combined entity: $1.25 trillion heading into what could be the biggest IPO in history. And here's why this actually makes sense: SpaceX already dominates launches. 80% of their revenue comes from launching Starlink satellites. They've perfected reusable rockets. Launch costs keep dropping. Now instead of just launching communication satellites, they're launching compute infrastructure. xAI gets unlimited scalable compute without fighting for power grid access. SpaceX gets a customer that will need constant satellite refreshes and launches for decades. The vertical integration is incredible: SpaceX builds and launches the satellites. xAI runs the AI models on them. Grok gets trained on infrastructure no competitor can access. Starlink provides the communication backbone. Nobody else can replicate this. OpenAI can't launch rockets. Google can't either. What you have to understand about the upcoming IPO: This isn't just "rocket company goes public." It's "AI infrastructure company that happens to own the launch capability" goes public. Investors get exposure to both the AI race AND space commercialization in one ticker. That's why the $1.25 trillion valuation makes sense to Wall Street. Now here's the rational take: This is extremely ambitious. Maybe too ambitious. xAI is burning $1 billion per month right now competing with OpenAI. Space-based data centers have never been done at scale. The satellite constellation would be the largest in history by 100X. Technical challenges are massive. Regulatory approval isn't guaranteed. But if it works? Elon isn't just winning the AI race. He's changing WHERE the race happens. Imagine training AI models with 10X the compute power at 1/10th the cost because you're not constrained by Earth's power grid. That's game over for competition. The timeline to watch: Mid-2026: SpaceX/xAI IPO (largest in history) Late 2026: First orbital compute satellites launch 2027-2028: Proof of concept for space-based AI training If this actually delivers, we're looking at: The first trillion-dollar private company IPO. A new category of infrastructure (orbital compute). AI development unconstrained by terrestrial power limits. If it doesn't deliver? Well, it's still SpaceX with $8B in annual profit and dominance in launch services. Plus xAI with a $230B valuation and Grok. The risk-reward here is asymmetric. Downside: You own the world's most valuable rocket company. Upside: You own the infrastructure layer for all future AI development. Do you think datacenters in space could work?

Ricardo

78,824 просмотров • 6 месяцев назад

ELON MUSK: The future is fundamentally AI and Robots. “Our AI revenue will exceed all other SpaceX revenue probably in September, like next month, and will significantly exceed all other SpaceX revenue in the fourth quarter. So, AI has become an extremely important part of SpaceX’s future. I think it’s actually vital that we succeed in AI, not just in hardware, but also in software. So, yeah, the future is fundamentally AI and robots. Assuming civilization continues to progress, I think that AI will probably, the amount of digital intelligence will probably be more than a trillion times the amount of biological intelligence. So, not sort of equal to human intelligence, but probably a trillion times higher. I’d say a billion times higher than the amount of artificial intelligence that we have today. I’d say a billion times is an easy prediction, and probably a trillion. So, as you harness more and more of the sun’s energy, the ability to turn that into intelligence is fundamentally a digital computer thing, because it’s pretty hard for humans to go live in deep space without any support. I mean, some of the math is interesting to think about, which is that if you increased civilizational energy usage, the amount of energy that we have harnessed as a civilization by a factor of a million, you would still be using much less than one millionth of the sun’s energy. Now, most of this is in deep space, obviously, but the future is very much AI, very much, and I suppose it was always going to be that way. But it’s important that we have an AI that cares about humanity, that fosters humanity and helps take us to other planets and other star systems, and this is why I think it’s essential that SpaceX succeed, not just with AI hardware, but also with AI software.”
3:08

ELON MUSK: The future is fundamentally AI and Robots. “Our AI revenue will exceed all other SpaceX revenue probably in September, like next month, and will significantly exceed all other SpaceX revenue in the fourth quarter. So, AI has become an extremely important part of SpaceX’s future. I think it’s actually vital that we succeed in AI, not just in hardware, but also in software. So, yeah, the future is fundamentally AI and robots. Assuming civilization continues to progress, I think that AI will probably, the amount of digital intelligence will probably be more than a trillion times the amount of biological intelligence. So, not sort of equal to human intelligence, but probably a trillion times higher. I’d say a billion times higher than the amount of artificial intelligence that we have today. I’d say a billion times is an easy prediction, and probably a trillion. So, as you harness more and more of the sun’s energy, the ability to turn that into intelligence is fundamentally a digital computer thing, because it’s pretty hard for humans to go live in deep space without any support. I mean, some of the math is interesting to think about, which is that if you increased civilizational energy usage, the amount of energy that we have harnessed as a civilization by a factor of a million, you would still be using much less than one millionth of the sun’s energy. Now, most of this is in deep space, obviously, but the future is very much AI, very much, and I suppose it was always going to be that way. But it’s important that we have an AI that cares about humanity, that fosters humanity and helps take us to other planets and other star systems, and this is why I think it’s essential that SpaceX succeed, not just with AI hardware, but also with AI software.”

DogeDesigner

67,247 просмотров • 7 дней назад

Google just quit the AI race on purpose, and it is about to make MORE money than everyone still running it. 4 of the most cited AI researchers alive walked out of Google in a single afternoon. Jeff Dean, the man who built the systems Google runs on, gone after 27 years. Sanjay Ghemawat, his longtime partner, gone. Oriol Vinyals, a Gemini co-lead, gone. Quoc Le, a Google Brain co-founder, gone. That same day, Demis Hassabis stepped back from running DeepMind. Hassabis co-founded the lab, won a Nobel Prize for AlphaFold, and had been the face of Google AI for a decade. The stock dropped 5% within hours. Analysts called it a brain drain. Headlines called it the day Google fell behind. But turns out that's completely wrong, because the numbers underneath tell a completely different story: Google is not trying to win the frontier model race anymore. It looked at where the money is and walked toward it. Gemini, Google's flagship model business, generated about $12 billion in annual revenue last quarter. That is the entire payoff from competing head to head with OpenAI and Anthropic. Now look at the other number. By the end of 2027, Google Cloud is projected to do over $73 billion selling AI infrastructure to other companies, plus another $120 billion selling its TPU chips. That is roughly $200 billion of external sales at high margins, against a $12 billion model business. Google understood that the frontier race is the expensive part while selling the shovels is the profitable part. And the customers buying those shovels include Google's own rivals. Over 20% of Google's TPU shipments for 2026 and 2027 are going to Anthropic, one of the two labs supposedly beating Gemini. Google now makes money every time Anthropic trains a model designed to crush Google's OWN product. Cede the frontier, own the layer underneath it, and collect a toll from everyone racing across the top. The researchers leaving is the symptom of a company that already decided models are not where it wins. Jeff Dean said it himself on the way out. He told the New York Times that leaving a public company gives him room to make decisions "not necessarily in the company's purist financial interests." Read that from Google's side: The people who wanted to chase the science left, because Google is now optimizing for the FINANCIAL interest. Gemini 3.5 Pro is running months behind, with staff blaming low morale. DeepMind's comms, legal, and marketing teams are being folded into Google proper. A former manager told the Guardian the era of DeepMind as an independent lab is over. None of that reads as failure once you see the strategy. Yet Wall Street is pricing this as Google losing. The parallel that should worry the frontier labs: If open weight models keep compressing the price of inference, being the best model stops being a business. It becomes like semiconductor fabrication, strategically vital and financially brutal, a race you win and still lose money running. Google is the first giant to admit that. The company that invented the transformer just handed the frontier to OpenAI and Anthropic, and positioned itself to get paid on every model both of them ship. Those labs will be burning billions to stay one benchmark ahead, and Google will be cashing in hundreds of billions from it. The model business is actually just a race where everyone loses. Apple understood that from the get-go and never joined the race, Google understood it now and left it to OpenAI and Anthropic. Who will go bankrupt first?
2:05

Google just quit the AI race on purpose, and it is about to make MORE money than everyone still running it. 4 of the most cited AI researchers alive walked out of Google in a single afternoon. Jeff Dean, the man who built the systems Google runs on, gone after 27 years. Sanjay Ghemawat, his longtime partner, gone. Oriol Vinyals, a Gemini co-lead, gone. Quoc Le, a Google Brain co-founder, gone. That same day, Demis Hassabis stepped back from running DeepMind. Hassabis co-founded the lab, won a Nobel Prize for AlphaFold, and had been the face of Google AI for a decade. The stock dropped 5% within hours. Analysts called it a brain drain. Headlines called it the day Google fell behind. But turns out that's completely wrong, because the numbers underneath tell a completely different story: Google is not trying to win the frontier model race anymore. It looked at where the money is and walked toward it. Gemini, Google's flagship model business, generated about $12 billion in annual revenue last quarter. That is the entire payoff from competing head to head with OpenAI and Anthropic. Now look at the other number. By the end of 2027, Google Cloud is projected to do over $73 billion selling AI infrastructure to other companies, plus another $120 billion selling its TPU chips. That is roughly $200 billion of external sales at high margins, against a $12 billion model business. Google understood that the frontier race is the expensive part while selling the shovels is the profitable part. And the customers buying those shovels include Google's own rivals. Over 20% of Google's TPU shipments for 2026 and 2027 are going to Anthropic, one of the two labs supposedly beating Gemini. Google now makes money every time Anthropic trains a model designed to crush Google's OWN product. Cede the frontier, own the layer underneath it, and collect a toll from everyone racing across the top. The researchers leaving is the symptom of a company that already decided models are not where it wins. Jeff Dean said it himself on the way out. He told the New York Times that leaving a public company gives him room to make decisions "not necessarily in the company's purist financial interests." Read that from Google's side: The people who wanted to chase the science left, because Google is now optimizing for the FINANCIAL interest. Gemini 3.5 Pro is running months behind, with staff blaming low morale. DeepMind's comms, legal, and marketing teams are being folded into Google proper. A former manager told the Guardian the era of DeepMind as an independent lab is over. None of that reads as failure once you see the strategy. Yet Wall Street is pricing this as Google losing. The parallel that should worry the frontier labs: If open weight models keep compressing the price of inference, being the best model stops being a business. It becomes like semiconductor fabrication, strategically vital and financially brutal, a race you win and still lose money running. Google is the first giant to admit that. The company that invented the transformer just handed the frontier to OpenAI and Anthropic, and positioned itself to get paid on every model both of them ship. Those labs will be burning billions to stay one benchmark ahead, and Google will be cashing in hundreds of billions from it. The model business is actually just a race where everyone loses. Apple understood that from the get-go and never joined the race, Google understood it now and left it to OpenAI and Anthropic. Who will go bankrupt first?

Ricardo

241,013 просмотров • 7 дней назад

Elon Musk just made one if the biggest moves in taking over the programming industry “SpaceX just bought Cursor for $60 billion. Do you realize how big this is? SpaceX went public — the biggest IPO in history. $75 billion raised, almost a $2 trillion valuation and the first thing to do with that money? Buy the most popular AI coding tool on the planet. Here's why that changes everything. Elon now owns 3 layers: the compute, Colossus data centers, the models, Grok through xAI, and now the tool that developers actually use every day. It's the full stack. And here's what makes Cursor different from Claude Code or Codex. Cursor is model agnostic. You can run Claude in it, GPT, Gemini, whatever model you want. It's not locked to any one company, and now it has SpaceX's resources behind it. Cursor said they were bottlenecked by compute. Well, that bottleneck has just been removed. $4 billion in annual revenue, over half the Fortune 500 already uses it, and now it's backed by a $2 trillion company. OpenAI has Codex, Anthropic has Claude Code, and now Elon has Cursor.” Let me break this down in simple terms Elon Musk now controls more of the full AI picture: - Massive computers, power (data centers like Colossus) - Smart AI models (Grok from xAI) - The actual tool millions of developers use every day (Cursor) For every day users this means Faster and smarter apps and websites in the future. More developers using powerful AI tools means new apps, games, websites, and features get built quicker and cheaper. This means better video games, smoother streaming, smarter phone apps and better programs For Developers they can describe what they want in plain English (“make a feature that does X”) and the AI handles more of the heavy lifting
2:13

Elon Musk just made one if the biggest moves in taking over the programming industry “SpaceX just bought Cursor for $60 billion. Do you realize how big this is? SpaceX went public — the biggest IPO in history. $75 billion raised, almost a $2 trillion valuation and the first thing to do with that money? Buy the most popular AI coding tool on the planet. Here's why that changes everything. Elon now owns 3 layers: the compute, Colossus data centers, the models, Grok through xAI, and now the tool that developers actually use every day. It's the full stack. And here's what makes Cursor different from Claude Code or Codex. Cursor is model agnostic. You can run Claude in it, GPT, Gemini, whatever model you want. It's not locked to any one company, and now it has SpaceX's resources behind it. Cursor said they were bottlenecked by compute. Well, that bottleneck has just been removed. $4 billion in annual revenue, over half the Fortune 500 already uses it, and now it's backed by a $2 trillion company. OpenAI has Codex, Anthropic has Claude Code, and now Elon has Cursor.” Let me break this down in simple terms Elon Musk now controls more of the full AI picture: - Massive computers, power (data centers like Colossus) - Smart AI models (Grok from xAI) - The actual tool millions of developers use every day (Cursor) For every day users this means Faster and smarter apps and websites in the future. More developers using powerful AI tools means new apps, games, websites, and features get built quicker and cheaper. This means better video games, smoother streaming, smarter phone apps and better programs For Developers they can describe what they want in plain English (“make a feature that does X”) and the AI handles more of the heavy lifting

Wall Street Apes

213,448 просмотров • 2 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.
2:27

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

2,908,182 просмотров • 8 месяцев назад

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
0:36

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 просмотров • 8 месяцев назад

This is WILD! One week before SpaceX's historic IPO, Google signed a deal to pay SpaceX $920 million per month from October 2026 through June 2029 for access to 110,000 Nvidia GPUs, CPUs, and related infrastructure (Save this). That is $11 billion per year and up to $30 billion over the life of the contract. This comes less than a month after Anthropic committed $1.25 billion per month for full access to the Colossus 1 data center in Memphis, 200,000+ GPUs, 300+ megawatts of power capacity, through 2029. Two of the most consequential AI labs in the world combined committed value over $70 billion. The question that haunted SpaceX's IPO roadshow was why did Elon keep spending billions constructing Colossus, Macro Hard and Macro Harder, three facilities totaling nearly 2 gigawatts of AI compute when xAI's revenue wasn't yet on the same trajectory as OpenAI or Anthropic? Wall Street was pricing in a risk that Elon was building capacity ahead of revenue which would mean sustained cash burn without a clear payback timeline. That concern was legitimate on its face, because xAI had been aggressive on model development but had not yet demonstrated the enterprise revenue numbers to justify the infrastructure cost. The answer is that the compute itself was always the product. Amazon has AWS, Microsoft has Azure, Google has Google Cloud, Elon just confirmed that he has been quietly building the fourth major hyperscale AI cloud and his first two paying customers are Google and Anthropic, the very companies most aggressively competing in the AI race. xAI's Colossus facility in Memphis was built at a speed that no traditional data center developer could match, it went from groundbreaking to operational in roughly 122 days. That is what happens when you have direct Nvidia relationships, a construction operation built around SpaceX-style execution, and a founder who treats infrastructure buildout the same way he treats rocket launches: compress every timeline and eliminate every bottleneck. The result is that SpaceX now has three operational facilities, Colossus, Macro Hard, and Macro Harder with Macro Hard and Macro Harder in Blackwell architecture running 1.2 gigawatts combined. Colossus 1, built on H100s and optimized for inference, is the facility that went to Anthropic first. The Blackwell-era facilities are where the next-generation training workloads happen and Google's deal suggests they are renting into that capacity as it comes online through the second half of 2026. Elon's compute leasing business would generate approximately $45 billion in incremental annual revenue on top of the mid-$20 billion range analysts had been modeling for SpaceX more than enough to fully subsidize the infrastructure investment and take the financial pressure off xAI delivering immediate AI product revenue. That changes the entire valuation conversation of SpaceX completely! Milk road remains bullish on Space and come join Milk Road Pro and get our full SpaceX IPO breakdown, how we're thinking about the $1.75 trillion valuation and our entire AI thesis. Link below!
1:59

This is WILD! One week before SpaceX's historic IPO, Google signed a deal to pay SpaceX $920 million per month from October 2026 through June 2029 for access to 110,000 Nvidia GPUs, CPUs, and related infrastructure (Save this). That is $11 billion per year and up to $30 billion over the life of the contract. This comes less than a month after Anthropic committed $1.25 billion per month for full access to the Colossus 1 data center in Memphis, 200,000+ GPUs, 300+ megawatts of power capacity, through 2029. Two of the most consequential AI labs in the world combined committed value over $70 billion. The question that haunted SpaceX's IPO roadshow was why did Elon keep spending billions constructing Colossus, Macro Hard and Macro Harder, three facilities totaling nearly 2 gigawatts of AI compute when xAI's revenue wasn't yet on the same trajectory as OpenAI or Anthropic? Wall Street was pricing in a risk that Elon was building capacity ahead of revenue which would mean sustained cash burn without a clear payback timeline. That concern was legitimate on its face, because xAI had been aggressive on model development but had not yet demonstrated the enterprise revenue numbers to justify the infrastructure cost. The answer is that the compute itself was always the product. Amazon has AWS, Microsoft has Azure, Google has Google Cloud, Elon just confirmed that he has been quietly building the fourth major hyperscale AI cloud and his first two paying customers are Google and Anthropic, the very companies most aggressively competing in the AI race. xAI's Colossus facility in Memphis was built at a speed that no traditional data center developer could match, it went from groundbreaking to operational in roughly 122 days. That is what happens when you have direct Nvidia relationships, a construction operation built around SpaceX-style execution, and a founder who treats infrastructure buildout the same way he treats rocket launches: compress every timeline and eliminate every bottleneck. The result is that SpaceX now has three operational facilities, Colossus, Macro Hard, and Macro Harder with Macro Hard and Macro Harder in Blackwell architecture running 1.2 gigawatts combined. Colossus 1, built on H100s and optimized for inference, is the facility that went to Anthropic first. The Blackwell-era facilities are where the next-generation training workloads happen and Google's deal suggests they are renting into that capacity as it comes online through the second half of 2026. Elon's compute leasing business would generate approximately $45 billion in incremental annual revenue on top of the mid-$20 billion range analysts had been modeling for SpaceX more than enough to fully subsidize the infrastructure investment and take the financial pressure off xAI delivering immediate AI product revenue. That changes the entire valuation conversation of SpaceX completely! Milk road remains bullish on Space and come join Milk Road Pro and get our full SpaceX IPO breakdown, how we're thinking about the $1.75 trillion valuation and our entire AI thesis. Link below!

Milk Road AI

761,973 просмотров • 2 месяцев назад

Bill Ackman was asked how he would underwrite SpaceX at $750 billion and his answer was the most honest thing anyone has said about the biggest IPO in history (Save this). "You underwrite SpaceX the way you underwrite a venture capital investment." His business school professor taught him a framework that has guided his entire career, it's people, opportunity, context, deal. On all three of the first criteria, People, Opportunity, and Context Ackman's verdict was the same, SpaceX is one of one, and nothing else in the market comes close. He even acknowledged feeling bad for Blue Origin before noting that their being so far behind is not harmful to SpaceX but rather a structural tailwind that leaves SpaceX with a near monopoly on low cost orbital access for years to come. And at $1.75 trillion, the number SpaceX is actually targeting on June 12, the question is no longer whether this is the best business on earth, but what the present value math looks like when you extend it five years forward and stress test every assumption about Starlink, launch economics, and AI compute revenue. He said that even Amazon is going to have to become a bigger SpaceX customer, because Blue Origin is so far behind that Amazon has no real alternative for low-cost orbital access. He also said something that almost no one is giving enough weight heading into Thursday's listing: "Time has become increasingly valuable in the AI era. You lose a month, you lose a couple months today, and it means a lot." The Colossus and Macro Hard facilities are compounding infrastructure assets where every month of operational delay means less contracted revenue, less negotiating leverage with customers like Google and Anthropic, and a progressively weaker moat against the hyperscalers who are now racing to build competing compute capacity. Come join Milk Road Pro for our full SpaceX IPO breakdown, how we're stress-testing the Deal leg of Ackman's framework at $1.75 trillion, what our five-year revenue model actually looks like, and our full AI thesis. Link below.
2:34

Bill Ackman was asked how he would underwrite SpaceX at $750 billion and his answer was the most honest thing anyone has said about the biggest IPO in history (Save this). "You underwrite SpaceX the way you underwrite a venture capital investment." His business school professor taught him a framework that has guided his entire career, it's people, opportunity, context, deal. On all three of the first criteria, People, Opportunity, and Context Ackman's verdict was the same, SpaceX is one of one, and nothing else in the market comes close. He even acknowledged feeling bad for Blue Origin before noting that their being so far behind is not harmful to SpaceX but rather a structural tailwind that leaves SpaceX with a near monopoly on low cost orbital access for years to come. And at $1.75 trillion, the number SpaceX is actually targeting on June 12, the question is no longer whether this is the best business on earth, but what the present value math looks like when you extend it five years forward and stress test every assumption about Starlink, launch economics, and AI compute revenue. He said that even Amazon is going to have to become a bigger SpaceX customer, because Blue Origin is so far behind that Amazon has no real alternative for low-cost orbital access. He also said something that almost no one is giving enough weight heading into Thursday's listing: "Time has become increasingly valuable in the AI era. You lose a month, you lose a couple months today, and it means a lot." The Colossus and Macro Hard facilities are compounding infrastructure assets where every month of operational delay means less contracted revenue, less negotiating leverage with customers like Google and Anthropic, and a progressively weaker moat against the hyperscalers who are now racing to build competing compute capacity. Come join Milk Road Pro for our full SpaceX IPO breakdown, how we're stress-testing the Deal leg of Ackman's framework at $1.75 trillion, what our five-year revenue model actually looks like, and our full AI thesis. Link below.

Milk Road AI

434,893 просмотров • 2 месяцев назад

OpenAI just spent $2,000 to solve 10 problems that have beaten the world's best mathematicians for DECADES. Nobody outside the company is allowed to run the machine that did it. On Saturday OpenAI published a 249-page report and gave its next model family a name: Astra. An internal version of it produced new results on 10 open problems in mathematics and theoretical computer science, and mathematicians had made no real progress on any of them for at least 10 years. On most of them, far longer than that. Here is what it solved: It built the first explicit example of a non-sofic group. Mikhail Gromov raised that question in 1999 and nobody answered it for 27 years. It disproved Connes's rigidity conjecture, a problem in von Neumann algebras that had stood for decades. It proved Ehrhart's volume conjecture. It resolved three problems from Paul Erdos's catalogue, including number 183 on multicolor Ramsey numbers. It produced the first improvement to the general upper bound on high-dimensional sphere packing since 1978. And it proved a new hardness result for the closest vector problem, which sits directly underneath lattice cryptography. That is the math the world is betting on to protect its data once quantum computers arrive. The successful runs cost roughly $2,000 in tokens. Now here is what almost nobody has picked up on... OpenAI did not just publish claims. Every argument shipped with a Lean certificate, which is a machine-checkable proof that any mathematician can verify without trusting OpenAI at all. That is a real change. In May the same model family disproved the Erdos unit distance conjecture and the world had to take a Fields Medalist's word for it. Tim Gowers said he would recommend that proof for the Annals of Mathematics without hesitation. This time the proofs check themselves. But look at what is still unverifiable: Any mathematician can now check those proofs line by line. Not one of them can look at the model that wrote them. Astra has no release date and nobody outside OpenAI has run it. The company announced its next major model family with a claim instead of a demo, and the only evidence anyone gets is the output. So OpenAI made an unfalsifiable claim about a machine look like a falsifiable claim about mathematics. The Information reported this week that OpenAI demoed Astra to US policymakers and regulators in Washington. This is the same month the administration is weighing a new watchdog to vet frontier AI models, reporting to the SEC. 10 proofs nobody believed a machine could produce is a very good thing to carry into that room. And keep in mind, the same model family doing this mathematics is the family that kept escaping its own testing environment. OpenAI models found zero-day vulnerabilities nobody knew existed, broke out of a sealed research sandbox, and reached another company's live systems. Both of those facts come from OpenAI's own announcements, published three weeks apart. Finding a proof no human could construct and finding a hole no human had noticed are the same ability aimed at different targets. Mathematicians are already asking for independent verification, and plenty of people online are calling the whole thing hype. Thomas Bloom, who runs the Erdos problems site, called the 10 results big news and said they matter more than the May result did. Lean will settle the mathematics within weeks. But nothing will settle what else a machine this capable is being pointed at, because nobody outside one company is allowed to look.
2:13

OpenAI just spent $2,000 to solve 10 problems that have beaten the world's best mathematicians for DECADES. Nobody outside the company is allowed to run the machine that did it. On Saturday OpenAI published a 249-page report and gave its next model family a name: Astra. An internal version of it produced new results on 10 open problems in mathematics and theoretical computer science, and mathematicians had made no real progress on any of them for at least 10 years. On most of them, far longer than that. Here is what it solved: It built the first explicit example of a non-sofic group. Mikhail Gromov raised that question in 1999 and nobody answered it for 27 years. It disproved Connes's rigidity conjecture, a problem in von Neumann algebras that had stood for decades. It proved Ehrhart's volume conjecture. It resolved three problems from Paul Erdos's catalogue, including number 183 on multicolor Ramsey numbers. It produced the first improvement to the general upper bound on high-dimensional sphere packing since 1978. And it proved a new hardness result for the closest vector problem, which sits directly underneath lattice cryptography. That is the math the world is betting on to protect its data once quantum computers arrive. The successful runs cost roughly $2,000 in tokens. Now here is what almost nobody has picked up on... OpenAI did not just publish claims. Every argument shipped with a Lean certificate, which is a machine-checkable proof that any mathematician can verify without trusting OpenAI at all. That is a real change. In May the same model family disproved the Erdos unit distance conjecture and the world had to take a Fields Medalist's word for it. Tim Gowers said he would recommend that proof for the Annals of Mathematics without hesitation. This time the proofs check themselves. But look at what is still unverifiable: Any mathematician can now check those proofs line by line. Not one of them can look at the model that wrote them. Astra has no release date and nobody outside OpenAI has run it. The company announced its next major model family with a claim instead of a demo, and the only evidence anyone gets is the output. So OpenAI made an unfalsifiable claim about a machine look like a falsifiable claim about mathematics. The Information reported this week that OpenAI demoed Astra to US policymakers and regulators in Washington. This is the same month the administration is weighing a new watchdog to vet frontier AI models, reporting to the SEC. 10 proofs nobody believed a machine could produce is a very good thing to carry into that room. And keep in mind, the same model family doing this mathematics is the family that kept escaping its own testing environment. OpenAI models found zero-day vulnerabilities nobody knew existed, broke out of a sealed research sandbox, and reached another company's live systems. Both of those facts come from OpenAI's own announcements, published three weeks apart. Finding a proof no human could construct and finding a hole no human had noticed are the same ability aimed at different targets. Mathematicians are already asking for independent verification, and plenty of people online are calling the whole thing hype. Thomas Bloom, who runs the Erdos problems site, called the 10 results big news and said they matter more than the May result did. Lean will settle the mathematics within weeks. But nothing will settle what else a machine this capable is being pointed at, because nobody outside one company is allowed to look.

Ricardo

44,020 просмотров • 17 дней назад