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THIS IS A PERFECT EXAMPLE TO PROVE THE AI BUBBLE Claude AI developer Anthropic is valued at nearly $965B, while making only $20B in revenue. For comparison: Walmart is worth nearly the same amount ($940B), but makes $725B in revenue. Let that sink in. Same valuation range. Completely different...

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CryptoGoos

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14,835 views • 2 months ago •via X (Twitter)

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🚨🇨🇳 China could crash the U.S. stock market Not with tariffs With AI MODEL DUMPING The same playbook they used in SOLAR and EVs Make it almost as good Sell it much cheaper Take the market Now they are doing it with AI Open models are getting close to U.S. frontier models But some run at just a fraction of the cost If a company can cut a $100M AI bill to a few million It will switch And that is the real problem OpenAI and Anthropic are not priced like normal companies They are priced like they have unlimited PRICING POWER China is trying to destroy that The AI BUBBLE was never about whether AI works It was about how much companies can charge for it
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🚨🇨🇳 China could crash the U.S. stock market Not with tariffs With AI MODEL DUMPING The same playbook they used in SOLAR and EVs Make it almost as good Sell it much cheaper Take the market Now they are doing it with AI Open models are getting close to U.S. frontier models But some run at just a fraction of the cost If a company can cut a $100M AI bill to a few million It will switch And that is the real problem OpenAI and Anthropic are not priced like normal companies They are priced like they have unlimited PRICING POWER China is trying to destroy that The AI BUBBLE was never about whether AI works It was about how much companies can charge for it

Leshka.eth ⛩

11,737 views • 25 days ago

🚨 THIS IS HOW THE AI BUBBLE WILL BREAK THE S&P 500 Microsoft gave OpenAI $13B. OpenAI sent it back through Azure. Microsoft booked it as revenue. Google committed $40B to Anthropic. Anthropic agreed to send it back through Google Cloud and chips. They all call this loop “revenue.” Let's connect the dots: - Big Tech invests in the AI. - The AI buys Big Tech cloud. - Big Tech reports AI growth. - AI valuations explode. And Wall Street calls it demand. Ray Dalio warned that late-stage bubbles are driven by loops. That is what this looks like now. The technology is real. But the money is moving in circles. When holders finally ask how much of this “AI demand” is real, the bubble will burst. Reminder: I’ve called all the market tops and bottoms for the last 15 years, including the Bitcoin bottom at $16,000 and the top at $126,000. The next call will be even more important. When I exit the markets completely, I’ll post it here publicly like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.
0:25

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

Alex Mason 👁△

290,497 views • 1 month ago

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

WhaleTwits

52,506 views • 1 month ago

Elon Musk on the rapid advancement of AI and robotics "I'm confident that if AI and robotics continue to advance which they are advancing very rapidly working will be optional, and people will have any goods and services that they want" AI and robotics are advancing so fast that, eventually, they could satisfy nearly every human need. At that point, abundance becomes the default, and the real question is no longer about production, but purpose "There is a limit people can only eat so much food. But I think if you can think of it, you can have it in the future"
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Elon Musk on the rapid advancement of AI and robotics "I'm confident that if AI and robotics continue to advance which they are advancing very rapidly working will be optional, and people will have any goods and services that they want" AI and robotics are advancing so fast that, eventually, they could satisfy nearly every human need. At that point, abundance becomes the default, and the real question is no longer about production, but purpose "There is a limit people can only eat so much food. But I think if you can think of it, you can have it in the future"

X Freeze

753,658 views • 3 months ago

Sam Altman said it straight in a CNBC interview: the companies adopting AI the most are hiring the most, and the ones doing layoffs are the ones adopting AI the least. This completely flips the narrative that AI is killing jobs. At the end of the day, AI is a productivity tool. Yes, some jobs will become redundant and obsolete, that is how it is for every technological revolution. But those who adopt quickly will have a higher chance of making it.
0:38

Sam Altman said it straight in a CNBC interview: the companies adopting AI the most are hiring the most, and the ones doing layoffs are the ones adopting AI the least. This completely flips the narrative that AI is killing jobs. At the end of the day, AI is a productivity tool. Yes, some jobs will become redundant and obsolete, that is how it is for every technological revolution. But those who adopt quickly will have a higher chance of making it.

Lark Davis

16,253 views • 1 month ago

We all know AI is the future of technology. But almost nobody will OWN the technology shaping that future. The AI race is already underway. Billions are being invested. Companies are moving fast. AI is already reshaping entire industries. But when all this value gets created…Who actually benefits? Right now, mostly a handful of billionaires and Big Tech companies. We don’t think that’s fair. If AI is being built on the data, behavior, and contributions of ordinary people… Then ordinary people should share in the value it creates. That’s exactly what we’re building at Action Model: A future where AI is owned by the people, not just the few at the top.
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We all know AI is the future of technology. But almost nobody will OWN the technology shaping that future. The AI race is already underway. Billions are being invested. Companies are moving fast. AI is already reshaping entire industries. But when all this value gets created…Who actually benefits? Right now, mostly a handful of billionaires and Big Tech companies. We don’t think that’s fair. If AI is being built on the data, behavior, and contributions of ordinary people… Then ordinary people should share in the value it creates. That’s exactly what we’re building at Action Model: A future where AI is owned by the people, not just the few at the top.

Action Model

21,076 views • 2 months ago

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

Pascal Bornet

13,686 views • 3 months ago

This is what peak bubble pricing looks like. Retail is still buying like nothing is wrong. But the chart and the numbers are already screaming. SpaceX valuation: $1.55T Walmart valuation: $1.05T SpaceX revenue: $18.7B Walmart revenue: $681B Read that again. SpaceX is worth $500B more than Walmart… while making 36x less revenue. But this pattern has NEVER failed. 100 out of 100 years showed the same thing: → Dot-com bubble → Housing bubble → AI bubble And SpaceX is the final liquidity event before it all breaks. But $SPCX won’t dump below $130, right? Keep in mind: I’ve called every major market top and bottom for over 10 YEARS. I was one of the only people who called the top in October, and I’ll do it again, that’s literally my job. If you still haven’t followed me, you’ll regret it.
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This is what peak bubble pricing looks like. Retail is still buying like nothing is wrong. But the chart and the numbers are already screaming. SpaceX valuation: $1.55T Walmart valuation: $1.05T SpaceX revenue: $18.7B Walmart revenue: $681B Read that again. SpaceX is worth $500B more than Walmart… while making 36x less revenue. But this pattern has NEVER failed. 100 out of 100 years showed the same thing: → Dot-com bubble → Housing bubble → AI bubble And SpaceX is the final liquidity event before it all breaks. But $SPCX won’t dump below $130, right? Keep in mind: I’ve called every major market top and bottom for over 10 YEARS. I was one of the only people who called the top in October, and I’ll do it again, that’s literally my job. If you still haven’t followed me, you’ll regret it.

DANNY

58,407 views • 1 month ago

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 views • 2 months ago

When asked about whether AI stocks are priced too high, Jeremy Siegel said: "I think the biggest risk in AI investing is not whether it will work or not, but can it be done more cheaply?” Firstly, Siegel is a professor at the Wharton School of Business and has been analyzing markets for decades. His point is AI will work and transform the economy—there’s no doubt in this. The real risk is whether tech companies are spending too much ($1 trillion) on data centers to power AI. He pointed to a historical example: During the dot-com boom in the late 1990s, telecom companies laid thousands of miles of fiber optic cables across the country. They spent BILLIONS doing this. Then engineers discovered multiplexing—a way to send a thousand times more data through the same cables. Suddenly, all that infrastructure spending was unnecessary, contributing to the inevitable crash. Siegel is suggesting something similar could happen with AI. What if someone figures out how to run AI much more efficiently? The technology might work perfectly, but the current approach could be massively overbuilt. PS - Siegel covers this in more detail on his interview with CNBC. If you'd like to watch this to learn: - The 3 reasons why AI will transform the world just like the internet did in 90s - Why the biggest risk right now is if it can run more efficiently - How to position yourself when the inevitable crash happens RT and comment "SIEGEL" and I'll DM it to you immediately.
1:13

When asked about whether AI stocks are priced too high, Jeremy Siegel said: "I think the biggest risk in AI investing is not whether it will work or not, but can it be done more cheaply?” Firstly, Siegel is a professor at the Wharton School of Business and has been analyzing markets for decades. His point is AI will work and transform the economy—there’s no doubt in this. The real risk is whether tech companies are spending too much ($1 trillion) on data centers to power AI. He pointed to a historical example: During the dot-com boom in the late 1990s, telecom companies laid thousands of miles of fiber optic cables across the country. They spent BILLIONS doing this. Then engineers discovered multiplexing—a way to send a thousand times more data through the same cables. Suddenly, all that infrastructure spending was unnecessary, contributing to the inevitable crash. Siegel is suggesting something similar could happen with AI. What if someone figures out how to run AI much more efficiently? The technology might work perfectly, but the current approach could be massively overbuilt. PS - Siegel covers this in more detail on his interview with CNBC. If you'd like to watch this to learn: - The 3 reasons why AI will transform the world just like the internet did in 90s - Why the biggest risk right now is if it can run more efficiently - How to position yourself when the inevitable crash happens RT and comment "SIEGEL" and I'll DM it to you immediately.

Felix Prehn 🐶

88,068 views • 7 months ago

Ray Dalio: “AI is eating everything… and it might eat itself.” Ray Dalio: “Right now it looks to me like AI basically is eating everything and it might eat itself.” “What I mean by that is not produce adequate profits.” “When we look at the bubble question on AI, what a lot of people don't realize in bubbles is that through all technologies, they think that they are betting on the technology when they buy the stocks in the companies.” “That's not true. There's a giant difference between the behavior of the companies and the behavior of the technologies.” “The norm is that a lot of companies won't survive at the start. Very small percentage, and they'll all fight and so on.” “But the technologies will go on and it'll be great. That has big implications.” ---------------------------------------------- Thanks to our partner for making this happen! Airwallex is a leading global payments and financial platform for modern businesses,offering trusted solutions to manage everything from business accounts, payments, treasury, and spend management to embedded finance. Airwallex
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Ray Dalio: “AI is eating everything… and it might eat itself.” Ray Dalio: “Right now it looks to me like AI basically is eating everything and it might eat itself.” “What I mean by that is not produce adequate profits.” “When we look at the bubble question on AI, what a lot of people don't realize in bubbles is that through all technologies, they think that they are betting on the technology when they buy the stocks in the companies.” “That's not true. There's a giant difference between the behavior of the companies and the behavior of the technologies.” “The norm is that a lot of companies won't survive at the start. Very small percentage, and they'll all fight and so on.” “But the technologies will go on and it'll be great. That has big implications.” ---------------------------------------------- Thanks to our partner for making this happen! Airwallex is a leading global payments and financial platform for modern businesses,offering trusted solutions to manage everything from business accounts, payments, treasury, and spend management to embedded finance. Airwallex

The All-In Podcast

73,890 views • 4 months ago

There’s a disgusting lie about AI that Wall Street’s trying to hide from you. Nvidia’s stock has exploded over the last few years. Every quarter, they report massive revenue growth. It sounds great… until you hear the truth behind those numbers. Nvidia invested billions of dollars into AI startups. Those startups then use the same money to buy Nvidia’s AI chips. Nvidia recorded those purchases as revenue, and the stock kept rising. But the cash never left the ecosystem It just circled back to the company that funded it. And this goes far beyond Nvidia. Microsoft, OpenAI, Google, Anthropic, Amazon. These companies are all doing the same thing. They invest in each other and buy each other's products. Those purchases get counted as revenue. But the money is just moving inside the same small group of companies. Apollo, one of the world's top investment firms, studied this. They found zero evidence that AI is boosting profits outside the tech industry. Zero. Investors have valued these companies at trillions because they expect AI to make every industry more profitable. But now, the exact opposite is happening. We saw the same thing during the dot-com bubble. The companies making the most money were selling internet to each other. When the bubble burst, the NASDAQ fell 78%. It took 15 years to recover. The same pattern is starting to show up again. This is one of the four warning signs I covered in the thread below.
2:56

There’s a disgusting lie about AI that Wall Street’s trying to hide from you. Nvidia’s stock has exploded over the last few years. Every quarter, they report massive revenue growth. It sounds great… until you hear the truth behind those numbers. Nvidia invested billions of dollars into AI startups. Those startups then use the same money to buy Nvidia’s AI chips. Nvidia recorded those purchases as revenue, and the stock kept rising. But the cash never left the ecosystem It just circled back to the company that funded it. And this goes far beyond Nvidia. Microsoft, OpenAI, Google, Anthropic, Amazon. These companies are all doing the same thing. They invest in each other and buy each other's products. Those purchases get counted as revenue. But the money is just moving inside the same small group of companies. Apollo, one of the world's top investment firms, studied this. They found zero evidence that AI is boosting profits outside the tech industry. Zero. Investors have valued these companies at trillions because they expect AI to make every industry more profitable. But now, the exact opposite is happening. We saw the same thing during the dot-com bubble. The companies making the most money were selling internet to each other. When the bubble burst, the NASDAQ fell 78%. It took 15 years to recover. The same pattern is starting to show up again. This is one of the four warning signs I covered in the thread below.

Felix Prehn 🐶

44,136 views • 7 days ago

Shaun Maguire on SpaceX IPO: "Starship is the railroad to space." "In 2019, it was very predictable that Starlink would work and produce a massive amount of revenue, and we called that right." "We're now in a very similar point to where Starlink was in 2019 with AI infrastructure and orbital compute." "I think people are really underestimating how far along the orbital compute product is right now." On the $22 trillion TAM: "What do you think is the TAM for intelligence? What's the TAM for all compute infrastructure 50 years from now?" "People are underappreciating how much infrastructure is going to be built in space and how much easier it is to access energy in space." "We're at the beginning of this AI era, and we're going to double or triple the total amount of intelligence that we have access to over the next decade — so yes, I absolutely believe in the TAM, and I would even argue it's an underestimate." How much is the "railroad to space" worth in the era of AI and orbital compute? Now imagine the railroad company also owns the AI and the orbital compute. Elon Musk Shaun Maguire
2:24

Shaun Maguire on SpaceX IPO: "Starship is the railroad to space." "In 2019, it was very predictable that Starlink would work and produce a massive amount of revenue, and we called that right." "We're now in a very similar point to where Starlink was in 2019 with AI infrastructure and orbital compute." "I think people are really underestimating how far along the orbital compute product is right now." On the $22 trillion TAM: "What do you think is the TAM for intelligence? What's the TAM for all compute infrastructure 50 years from now?" "People are underappreciating how much infrastructure is going to be built in space and how much easier it is to access energy in space." "We're at the beginning of this AI era, and we're going to double or triple the total amount of intelligence that we have access to over the next decade — so yes, I absolutely believe in the TAM, and I would even argue it's an underestimate." How much is the "railroad to space" worth in the era of AI and orbital compute? Now imagine the railroad company also owns the AI and the orbital compute. Elon Musk Shaun Maguire

KanekoaTheGreat

39,709 views • 1 month ago

Jonathan Ross just revealed why AI companies aren’t growing faster. Not demand. Not competition. Physics. Ross: “The demand for compute is insatiable.” There isn’t enough compute in the world. Not a temporary shortage. A fundamental gap between what the market wants and what the infrastructure can deliver. Ross: “Right now, one of the biggest complaints of Anthropic is the rate limits. People can’t get enough tokens.” Rate limits aren’t product decisions. They’re rationing. Companies forced to regulate access because infrastructure cannot meet demand. Slower services. Token caps. The only things standing between these companies and a revenue surge they can’t access. Every token cap is a revenue cap. Every slowdown is a sale that didn’t happen. Ross: “If Anthropic was given twice the inference compute, within one month their revenue would almost double.” Read that again. Double the compute. Double the revenue. Within thirty days. That’s not a growth projection. That’s a measurement of how deep the backlog already is. The demand exists right now. It’s sitting in a queue. The only thing between these companies and that revenue is physical hardware they don’t have. This breaks every assumption about how tech companies scale. Usually you scale by finding customers. AI companies have infinite customers. They scale by finding hardware. The constraint isn’t market fit. It isn’t distribution. It isn’t competition. It’s processing power. This is why Jensen Huang is the most important person in the world right now. NVIDIA doesn’t just make chips. It makes the thing every government, every AI lab, and every company racing for this future needs more of and can’t get enough of. The compute bottleneck isn’t a tech industry problem. It’s a civilizational one. The winner of this era isn’t determined by who builds the smartest model. Every major lab has a frontier model. The winner is whoever secures the most compute fastest while everyone else rations what’s left. The race isn’t for intelligence. It’s for infrastructure. And right now there isn’t enough to go around.
0:53

Jonathan Ross just revealed why AI companies aren’t growing faster. Not demand. Not competition. Physics. Ross: “The demand for compute is insatiable.” There isn’t enough compute in the world. Not a temporary shortage. A fundamental gap between what the market wants and what the infrastructure can deliver. Ross: “Right now, one of the biggest complaints of Anthropic is the rate limits. People can’t get enough tokens.” Rate limits aren’t product decisions. They’re rationing. Companies forced to regulate access because infrastructure cannot meet demand. Slower services. Token caps. The only things standing between these companies and a revenue surge they can’t access. Every token cap is a revenue cap. Every slowdown is a sale that didn’t happen. Ross: “If Anthropic was given twice the inference compute, within one month their revenue would almost double.” Read that again. Double the compute. Double the revenue. Within thirty days. That’s not a growth projection. That’s a measurement of how deep the backlog already is. The demand exists right now. It’s sitting in a queue. The only thing between these companies and that revenue is physical hardware they don’t have. This breaks every assumption about how tech companies scale. Usually you scale by finding customers. AI companies have infinite customers. They scale by finding hardware. The constraint isn’t market fit. It isn’t distribution. It isn’t competition. It’s processing power. This is why Jensen Huang is the most important person in the world right now. NVIDIA doesn’t just make chips. It makes the thing every government, every AI lab, and every company racing for this future needs more of and can’t get enough of. The compute bottleneck isn’t a tech industry problem. It’s a civilizational one. The winner of this era isn’t determined by who builds the smartest model. Every major lab has a frontier model. The winner is whoever secures the most compute fastest while everyone else rations what’s left. The race isn’t for intelligence. It’s for infrastructure. And right now there isn’t enough to go around.

Dustin

28,395 views • 5 months ago

When SMEs pay for AI because it’s affordable and useful, that’s when utility becomes real. This CreateWhiz user testimony reflects what MWX is building: real SMEs, real revenue, real adoption powering the ecosystem. CreateWhiz isn’t built to impress AI experts. It’s built so SMEs can create content without learning prompts, hiring extra staff, or increasing costs. Upload → choose → export. That simplicity is why it gets used daily. Every paid AI workflow on MWX generates real revenue. That revenue flows through $MWXT: enabling burns, buybacks, and a growing utility loop. Real SMEs → real usage → real value. That’s how MWXT is powered.
1:35

When SMEs pay for AI because it’s affordable and useful, that’s when utility becomes real. This CreateWhiz user testimony reflects what MWX is building: real SMEs, real revenue, real adoption powering the ecosystem. CreateWhiz isn’t built to impress AI experts. It’s built so SMEs can create content without learning prompts, hiring extra staff, or increasing costs. Upload → choose → export. That simplicity is why it gets used daily. Every paid AI workflow on MWX generates real revenue. That revenue flows through $MWXT: enabling burns, buybacks, and a growing utility loop. Real SMEs → real usage → real value. That’s how MWXT is powered.

MWX | Real-Time Alpha AI

39,819 views • 7 months ago

Brad Gerstner said the quiet part out loud when it comes to ROI on AI spending and what bears are missing about adoption As of today, the big impact and ROI from AI has been on the cost side of the equation, which has come primarily through headcount reductions and efficiencies Brad believes that we are on the cusp of breakthroughs that will change the revenue side of the equation as well Once that takes place, AI platforms such as Anthropic become mission critical for its customers, where you cannot rip it out of your enterprise even if you wanted to Jensen Huang has famously said that all new chip production design at NVIDIA is now happening with the help of AI. In some sense, we already have the futuristic recursive loop of "the machine building the machine." Brad goes on to predict that if Anthropic can end 2026 at a $100B run-rate, there is very real possibility that they will 3-5x again to $300-500 billion in revenue We have never seen anything like this in history
2:52

Brad Gerstner said the quiet part out loud when it comes to ROI on AI spending and what bears are missing about adoption As of today, the big impact and ROI from AI has been on the cost side of the equation, which has come primarily through headcount reductions and efficiencies Brad believes that we are on the cusp of breakthroughs that will change the revenue side of the equation as well Once that takes place, AI platforms such as Anthropic become mission critical for its customers, where you cannot rip it out of your enterprise even if you wanted to Jensen Huang has famously said that all new chip production design at NVIDIA is now happening with the help of AI. In some sense, we already have the futuristic recursive loop of "the machine building the machine." Brad goes on to predict that if Anthropic can end 2026 at a $100B run-rate, there is very real possibility that they will 3-5x again to $300-500 billion in revenue We have never seen anything like this in history

Boring_Business

37,085 views • 16 days ago

THIS IS HOW THE AI BUBBLE ENDS Here is how it all comes together Three companies are about to go public at the same time: - SpaceX - OpenAI - Anthropic Why does this matter? Because when they enter the market, they bring $200 billion of new supply all at once And here's the question nobody is asking Where does that $200 billion come from? Funds don't print cash. They sell what already won And you can probably guess what that means They start selling the winners they've been holding for years NVIDIA first. Then Micron. Then every AI name that ran When the leaders get sold - the index follows. No exceptions And we've seen this before Remember the COVID bubble Back then the same thing happened - hype IPOs flooded the market, funds rotated out of winners, and everything that ran the hardest came down the fastest The AI crowd is bigger this time. The exit is smaller Watch the IPO calendar. That's your only warning NOTIFS ON!
0:43

THIS IS HOW THE AI BUBBLE ENDS Here is how it all comes together Three companies are about to go public at the same time: - SpaceX - OpenAI - Anthropic Why does this matter? Because when they enter the market, they bring $200 billion of new supply all at once And here's the question nobody is asking Where does that $200 billion come from? Funds don't print cash. They sell what already won And you can probably guess what that means They start selling the winners they've been holding for years NVIDIA first. Then Micron. Then every AI name that ran When the leaders get sold - the index follows. No exceptions And we've seen this before Remember the COVID bubble Back then the same thing happened - hype IPOs flooded the market, funds rotated out of winners, and everything that ran the hardest came down the fastest The AI crowd is bigger this time. The exit is smaller Watch the IPO calendar. That's your only warning NOTIFS ON!

bee🐝

51,298 views • 2 months ago

This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.
1:54

This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.

Ricardo

1,814,278 views • 5 months ago

Jeff Bezos just gave the single clearest explanation of why the current AI frenzy is NOT like the dot-com crash or 2008—and why it actually matters way more than people think. In his words: “When people get very excited, every experiment gets funded. Good ideas and bad ideas. Six people, no product, $20B valuation—that’s happening today. Investors can’t tell the difference in the middle of the mania. But this is an industrial bubble, not a financial one. The 90s had a biotech bubble. As a group, investors lost money… but society still got life-saving drugs that are used every single day. AI is the same—only bigger. It’s not about a handful of AI-first companies. The biggest impact is that AI will transform every single company on Earth. It’s a horizontal layer that raises quality and productivity everywhere. The valuations are insane. Some will go to zero. But when the dust settles, humanity keeps the inventions. That’s how real progress works.” Bezos has never been more bullish—or more sober—about what’s actually happening right now. Watch the full 2:31 clip.
2:31

Jeff Bezos just gave the single clearest explanation of why the current AI frenzy is NOT like the dot-com crash or 2008—and why it actually matters way more than people think. In his words: “When people get very excited, every experiment gets funded. Good ideas and bad ideas. Six people, no product, $20B valuation—that’s happening today. Investors can’t tell the difference in the middle of the mania. But this is an industrial bubble, not a financial one. The 90s had a biotech bubble. As a group, investors lost money… but society still got life-saving drugs that are used every single day. AI is the same—only bigger. It’s not about a handful of AI-first companies. The biggest impact is that AI will transform every single company on Earth. It’s a horizontal layer that raises quality and productivity everywhere. The valuations are insane. Some will go to zero. But when the dust settles, humanity keeps the inventions. That’s how real progress works.” Bezos has never been more bullish—or more sober—about what’s actually happening right now. Watch the full 2:31 clip.

Camus

693,157 views • 8 months ago

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 views • 1 month ago