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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 просмотров • 1 месяц назад •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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🚨 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.

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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.

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16,080 просмотров • 2 месяцев назад

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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.

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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

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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.
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28,395 просмотров • 4 месяцев назад

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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 просмотров • 1 месяц назад

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.
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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 просмотров • 6 месяцев назад

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 просмотров • 4 дней назад

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

1,813,369 просмотров • 5 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 • 1 месяц назад

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 просмотров • 1 месяц назад

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 просмотров • 7 месяцев назад

$65B fund CEO: "AI is now doing in hours what finance PhDs used to do in months" He spent 26 minutes at Stanford explaining why even the biggest skeptics are running out of time to ignore this Ken Griffin built Citadel into one of the most successful hedge funds ever couple of months ago he called AI "just a productivity tool", but since then something has changed: > we're already at the stage where AI is replacing not mid-tier jobs but extraordinarily high-skilled ones > in the last few months AI integration at Citadel grew faster than anyone expected > his exact words: the issue with AI is that humans are now the horses any company refusing to adopt AI right now will fall behind competitors who do, that gap is only going to grow the same is true for people, an employee who knows how to use AI will outperform one who doesn't the same way AI-first companies are outperforming everyone else that's exactly why I put together a step-by-step guide on how to set up and use Claude the right way useful whether you've never touched it or you've been using it for a while full guide in the article below
26:09

$65B fund CEO: "AI is now doing in hours what finance PhDs used to do in months" He spent 26 minutes at Stanford explaining why even the biggest skeptics are running out of time to ignore this Ken Griffin built Citadel into one of the most successful hedge funds ever couple of months ago he called AI "just a productivity tool", but since then something has changed: > we're already at the stage where AI is replacing not mid-tier jobs but extraordinarily high-skilled ones > in the last few months AI integration at Citadel grew faster than anyone expected > his exact words: the issue with AI is that humans are now the horses any company refusing to adopt AI right now will fall behind competitors who do, that gap is only going to grow the same is true for people, an employee who knows how to use AI will outperform one who doesn't the same way AI-first companies are outperforming everyone else that's exactly why I put together a step-by-step guide on how to set up and use Claude the right way useful whether you've never touched it or you've been using it for a while full guide in the article below

Anatoli Kopadze

35,718 просмотров • 2 месяцев назад