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"Being too early is the same thing as being wrong." Amplitude CEO Spenser Skates breaks down the math: Cursor (AI IDE): ~$1 Billion Revenue Devin (AI Agent): ~$100–200 Million Revenue Why the massive gap? One met developers where they live. The other tried to replace the environment entirely. "If... show more

Forward Future

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46,682 просмотров • 8 месяцев назад •via X (Twitter)

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Andy Jassy explains why Amazon is willing to look inefficient for years: Cramer: "You spend $200 billion and you actually believe it is going to pay off." Jassy's answer is the part most operators miss. AI is not being treated like a normal product cycle. He compares it to AWS: After 3 years, AWS was at about $56M in revenue. After 3 years, Amazon's AI run-rate is over $15B. 260x larger than AWS at the same point. That is why Amazon is willing to absorb short-term capex pain. The public market sees a giant expense line. The operator sees infrastructure being built ahead of monetization. This is one of the hardest parts of company building: Knowing when the numbers look ugly because the bet is wrong... and when they look ugly because you are early to a compounding curve. After building $300M+ businesses, this is the pattern I respect most: The best operators are not reckless. They just understand the cash cycle better than the audience judging them. They know when a cost is actually an asset in disguise.

Andy Jassy explains why Amazon is willing to look inefficient for years: Cramer: "You spend $200 billion and you actually believe it is going to pay off." Jassy's answer is the part most operators miss. AI is not being treated like a normal product cycle. He compares it to AWS: After 3 years, AWS was at about $56M in revenue. After 3 years, Amazon's AI run-rate is over $15B. 260x larger than AWS at the same point. That is why Amazon is willing to absorb short-term capex pain. The public market sees a giant expense line. The operator sees infrastructure being built ahead of monetization. This is one of the hardest parts of company building: Knowing when the numbers look ugly because the bet is wrong... and when they look ugly because you are early to a compounding curve. After building $300M+ businesses, this is the pattern I respect most: The best operators are not reckless. They just understand the cash cycle better than the audience judging them. They know when a cost is actually an asset in disguise.

andrew engler

47,581 просмотров • 2 месяцев 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 $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.$

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

1,814,969 просмотров • 6 месяцев назад

Cognition has signed a definitive agreement to acquire Windsurf. The acquisition includes Windsurf’s IP, product, trademark and brand, and strong business. Above all, it includes Windsurf’s world-class people, whom we’re privileged to welcome to our team. We are also honoring their talent and hard work in building Windsurf into the great business it is today. This transaction is structured so that 100% of Windsurf employees will participate financially. They will also have all vesting cliffs waived and will receive fully accelerated vesting for their work to date. At Cognition we have focused on developing robust and secure autonomous agents, while Windsurf has pioneered the agentic IDE. Devin + Windsurf are a powerful combination for the developers we serve. Working side by side, we’ll soon enable you to plan tasks in an IDE powered by Devin’s codebase understanding, delegate chunks of work to multiple Devins in parallel, complete the highest-leverage parts yourself with the help of autocomplete, and stitch it all back together in the same IDE. Cognition and Windsurf are united behind a shared vision for the future of software engineering, and there’s never been a better time to build. Welcome to our new colleagues from Windsurf!

Cognition

3,050,353 просмотров • 1 год назад

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.

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 🐶

44,470 просмотров • 24 дней назад

you are collecting AI tools, like they are the skill they are not the tools are all sliding to the same place, by next quarter they are interchangeable what is not, is knowing which output is actually good and being willing to kill the rest the model makes ten versions, it cannot tell you which one to send

you are collecting AI tools, like they are the skill they are not the tools are all sliding to the same place, by next quarter they are interchangeable what is not, is knowing which output is actually good and being willing to kill the rest the model makes ten versions, it cannot tell you which one to send

Lagosaur

10,918 просмотров • 23 дней назад

Gavin Baker on the SpaceX situation: "Wall Street consensus is $73 billion in revenue - if they bring on 3 gigawatts of power next year that's $150 billion - that's not in the model" this is him explaining why SpaceX could double what the Street expects, why intelligence per dollar will define the future of AI, and why betting against Elon has destroyed entire funds "open source models fundamentally just shift margin from the model layer to the infrastructure layer - if you have cheaper tokens we're going to consume more of them - we are structurally short compute" "the Cursor acquisition for $60 billion is looking very smart - that was $3 billion in annual revenue when they bought it - I think it's probably materially higher" "there's a graveyard of funds that shut down because they were Tesla short" bookmark & watch the full conversation ↓

Gavin Baker on the SpaceX situation: "Wall Street consensus is $73 billion in revenue - if they bring on 3 gigawatts of power next year that's $150 billion - that's not in the model" this is him explaining why SpaceX could double what the Street expects, why intelligence per dollar will define the future of AI, and why betting against Elon has destroyed entire funds "open source models fundamentally just shift margin from the model layer to the infrastructure layer - if you have cheaper tokens we're going to consume more of them - we are structurally short compute" "the Cursor acquisition for $60 billion is looking very smart - that was $3 billion in annual revenue when they bought it - I think it's probably materially higher" "there's a graveyard of funds that shut down because they were Tesla short" bookmark & watch the full conversation ↓

Сarm1ne

771,173 просмотров • 23 дней назад

CoreWeave started as a crypto miner. Then they pivoted their GPUs into AI. $CRWV revenue went from $16M to $8B in 3 years. They sell ONE thing: compute. The thing AI literally cannot exist without. If you believe AGI is coming, you should own $CRWV. Leopold's already in.

CoreWeave started as a crypto miner. Then they pivoted their GPUs into AI. $CRWV revenue went from $16M to $8B in 3 years. They sell ONE thing: compute. The thing AI literally cannot exist without. If you believe AGI is coming, you should own $CRWV. Leopold's already in.

EllioTrades Clips

19,645 просмотров • 2 месяцев назад

Avoca (W23) is building what it calls the AI workforce for the physical economy, starting with home services. In just a few years, the company has grown to eight figures in revenue and recently raised over $125 million at a $1 billion valuation. In this fireside, co-founders Apurva Shrivastava and Tyson Chen sit down with Garry Tan to share how they found product-market fit by helping businesses turn missed calls into revenue. They explain why AI is expanding what software can do, pushing past the 1% of wallet that traditional software captures, and why they see it as one of the biggest opportunities for founders. 01:28 - Finding the Right Market 03:25 - Why AI Is Bigger Than SaaS 06:59 - The AI Job Story Nobody Talks About 11:53 - How the Founders Met 16:59 - The Pivot 21:47 - Customer Love Beats Market Size 25:31 - Building an AI Workforce 29:35 - Why Customer Obsession Wins 34:12 - Growing to Eight Figures 37:22 - The Vision Beyond Home Services 38:54 - Building a Generational Company

Avoca (W23) is building what it calls the AI workforce for the physical economy, starting with home services. In just a few years, the company has grown to eight figures in revenue and recently raised over $125 million at a $1 billion valuation. In this fireside, co-founders Apurva Shrivastava and Tyson Chen sit down with Garry Tan to share how they found product-market fit by helping businesses turn missed calls into revenue. They explain why AI is expanding what software can do, pushing past the 1% of wallet that traditional software captures, and why they see it as one of the biggest opportunities for founders. 01:28 - Finding the Right Market 03:25 - Why AI Is Bigger Than SaaS 06:59 - The AI Job Story Nobody Talks About 11:53 - How the Founders Met 16:59 - The Pivot 21:47 - Customer Love Beats Market Size 25:31 - Building an AI Workforce 29:35 - Why Customer Obsession Wins 34:12 - Growing to Eight Figures 37:22 - The Vision Beyond Home Services 38:54 - Building a Generational Company

Y Combinator

84,506 просмотров • 1 месяц назад

🚨 THEY TOLD YOU THE DATA CENTERS WERE FOR AI... BUT FOLLOW THE WATER Something about this feels VERY wrong. We're being told the biggest corporations on Earth are spending hundreds of billions of dollars building massive AI infrastructure because artificial intelligence needs more computing power. That's the official explanation. But while everyone is focused on AI, almost nobody is paying attention to what these facilities are consuming. Water. Enormous amounts of it. At the same time we're being warned about droughts, shrinking reservoirs, water restrictions, and future shortages. The explanation is simple: The servers get hot. The facilities need cooling. The cooling requires water. Case closed. Except some people think AI is the perfect cover story. While the public debates chatbots and robots, powerful institutions appear to be racing toward the one resource every human being needs to survive. Not oil. Not gold. Not land. Water. You can live without social media. You can live without artificial intelligence. You can live without most of the technology being sold to you today. You cannot live without water. And if water really is becoming the most valuable resource on Earth, then whoever controls it could control everything that depends on it. The official story is that this is an AI revolution. The conspiracy theory is that AI is simply the headline while a much larger resource grab unfolds in plain sight. What do they know about the future of water that the public doesn't?

🚨 THEY TOLD YOU THE DATA CENTERS WERE FOR AI... BUT FOLLOW THE WATER Something about this feels VERY wrong. We're being told the biggest corporations on Earth are spending hundreds of billions of dollars building massive AI infrastructure because artificial intelligence needs more computing power. That's the official explanation. But while everyone is focused on AI, almost nobody is paying attention to what these facilities are consuming. Water. Enormous amounts of it. At the same time we're being warned about droughts, shrinking reservoirs, water restrictions, and future shortages. The explanation is simple: The servers get hot. The facilities need cooling. The cooling requires water. Case closed. Except some people think AI is the perfect cover story. While the public debates chatbots and robots, powerful institutions appear to be racing toward the one resource every human being needs to survive. Not oil. Not gold. Not land. Water. You can live without social media. You can live without artificial intelligence. You can live without most of the technology being sold to you today. You cannot live without water. And if water really is becoming the most valuable resource on Earth, then whoever controls it could control everything that depends on it. The official story is that this is an AI revolution. The conspiracy theory is that AI is simply the headline while a much larger resource grab unfolds in plain sight. What do they know about the future of water that the public doesn't?

HustleBitch

259,404 просмотров • 1 месяц 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!

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

Jane Street made $39.6 billion in revenue, they just signed a $6 billion deal for GPUs - and they say they need even more this is their co-head of technology taking you inside their data center and explaining how they actually trade their systems respond in under 100 nanoseconds "if you attached an oscilloscope to the wire, the packet starts to leave before it's done being consumed" "our most profitable days happen when weird stuff happens and the world goes crazy that's when you get paid most for providing liquidity" the article below breaks down why 95% of traders still lose and how AI-powered systems are finally changing that ↓

Jane Street made $39.6 billion in revenue, they just signed a $6 billion deal for GPUs - and they say they need even more this is their co-head of technology taking you inside their data center and explaining how they actually trade their systems respond in under 100 nanoseconds "if you attached an oscilloscope to the wire, the packet starts to leave before it's done being consumed" "our most profitable days happen when weird stuff happens and the world goes crazy that's when you get paid most for providing liquidity" the article below breaks down why 95% of traders still lose and how AI-powered systems are finally changing that ↓

Сarm1ne

540,273 просмотров • 2 месяцев 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!

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 • 2 месяцев назад

Most people are terrified AI will take their jobs because they confuse their tasks with their purpose. Jensen Huang explains it perfectly: If you watched a CEO all day, you would think their job is "typist" because they spend most of their time typing emails. If AI automates typing, the CEO doesn't lose their job. They just have more time to lead. The same applies to everyone. When AI automates the tasks, it enhances the purpose. Stop measuring your value by your to-do list. Your value is the purpose behind it.

Most people are terrified AI will take their jobs because they confuse their tasks with their purpose. Jensen Huang explains it perfectly: If you watched a CEO all day, you would think their job is "typist" because they spend most of their time typing emails. If AI automates typing, the CEO doesn't lose their job. They just have more time to lead. The same applies to everyone. When AI automates the tasks, it enhances the purpose. Stop measuring your value by your to-do list. Your value is the purpose behind it.

Lucian Fogoros

359,283 просмотров • 6 месяцев назад

"The question is, why are you trying to get the Muhammad Ali Act changed or removed? The strange thing about that act is that on every show you have to declare to the fighters on the card the revenue of the event, which is quite unique. There isn't really a problem with that in the boxing world because a significant proportion of the revenue is paid to the athlete... I think they will think that fighters are overpaid because they are in relation to the UFC and MMA talent." Eddie Hearn on TKO's ambitions to alter the Ali Act.

"The question is, why are you trying to get the Muhammad Ali Act changed or removed? The strange thing about that act is that on every show you have to declare to the fighters on the card the revenue of the event, which is quite unique. There isn't really a problem with that in the boxing world because a significant proportion of the revenue is paid to the athlete... I think they will think that fighters are overpaid because they are in relation to the UFC and MMA talent." Eddie Hearn on TKO's ambitions to alter the Ali Act.

Ariel Helwani

474,767 просмотров • 11 месяцев назад

Ridge CEO Sean Frank says he'd be willing to give OpenAI a 40% cut of his revenue for ad placement in GPT, because he's already giving 50% to Meta to sell his products. "The beauty of the Facebook ad product is that they figured out a way to take half of everybody's revenue." "They figured out exactly how much money they could take from everybody at the optimal level, and that's why they do $100 billion a year in revenue." "So if the offer from ChatGPT is 'Give us 40% of your revenue, and we'll give you new customers you wouldn't get otherwise,' I would take that deal because I'm already giving Mark Zuckerberg 50%."

Ridge CEO Sean Frank says he'd be willing to give OpenAI a 40% cut of his revenue for ad placement in GPT, because he's already giving 50% to Meta to sell his products. "The beauty of the Facebook ad product is that they figured out a way to take half of everybody's revenue." "They figured out exactly how much money they could take from everybody at the optimal level, and that's why they do $100 billion a year in revenue." "So if the offer from ChatGPT is 'Give us 40% of your revenue, and we'll give you new customers you wouldn't get otherwise,' I would take that deal because I'm already giving Mark Zuckerberg 50%."

TBPN

43,375 просмотров • 6 месяцев назад

Marc Andreessen on the imperative of speed in AI adoption: "Both the AI utopians and the AI doomers are far too optimistic." "They believe that because the technology makes something possible, 8 billion people all of a sudden are going to change how they behave. It's like—no. So much of how the existing economy works is just wired in." "We're going to be lucky as a society if AI adoption happens quickly. Because if it doesn't, what we're going to have is stagnation." Marc Andreessen 🇺🇸 with Latent.Space

Marc Andreessen on the imperative of speed in AI adoption: "Both the AI utopians and the AI doomers are far too optimistic." "They believe that because the technology makes something possible, 8 billion people all of a sudden are going to change how they behave. It's like—no. So much of how the existing economy works is just wired in." "We're going to be lucky as a society if AI adoption happens quickly. Because if it doesn't, what we're going to have is stagnation." Marc Andreessen 🇺🇸 with Latent.Space

a16z

70,510 просмотров • 4 месяцев назад

Gavin Baker: "the cheapest producer of intelligence will win the AI race if Anthropic's neocloud and cloud providers were using Arya, maybe they wouldn't have $30 billion in revenue - they'd be at $60 billion" this is him naming the companies he just bought and giving investing advice His words: "I'm a Crusoe, CoreWeave and Nebius shareholder - I love you all" "Apple isn't worth three trillion because they make the cheapest smartphones. Nvidia isn't worth five trillion because they make the cheapest chips - they're just the best - AI is fundamentally different" "why was I one of the earliest investors in Tesla and Nvidia? Musk - said "that's crazy" and put the battery at the bottom of the car Huang - gaming chips and AI chips needed the same math - he bet everything on it" "every 100 millisecond delay in Google search results cost them 1% of revenue" "fortune favors the bold. Be bold" bookmark & watch today ↓

Gavin Baker: "the cheapest producer of intelligence will win the AI race if Anthropic's neocloud and cloud providers were using Arya, maybe they wouldn't have $30 billion in revenue - they'd be at $60 billion" this is him naming the companies he just bought and giving investing advice His words: "I'm a Crusoe, CoreWeave and Nebius shareholder - I love you all" "Apple isn't worth three trillion because they make the cheapest smartphones. Nvidia isn't worth five trillion because they make the cheapest chips - they're just the best - AI is fundamentally different" "why was I one of the earliest investors in Tesla and Nvidia? Musk - said "that's crazy" and put the battery at the bottom of the car Huang - gaming chips and AI chips needed the same math - he bet everything on it" "every 100 millisecond delay in Google search results cost them 1% of revenue" "fortune favors the bold. Be bold" bookmark & watch today ↓

bodila

176,787 просмотров • 12 дней назад

AI cannot make money. ChatGPT costs billions to run. Generates almost nothing in return. So why is Amazon, Microsoft, Google and Meta tripling their AI investment every year? Because they are all investing in each other. It is a circle. Nobody is making money. Everyone is pretending they will. There is only one solution to a bubble this big. The government. Three days after Trump's inauguration — Operation Stargate. $500 billion for AI data centers. Not because AI is profitable. Because the government needs the surveillance infrastructure that AI makes possible. AI needed the government to survive. The government needed AI to control. They found each other. And you are paying for it.

AI cannot make money. ChatGPT costs billions to run. Generates almost nothing in return. So why is Amazon, Microsoft, Google and Meta tripling their AI investment every year? Because they are all investing in each other. It is a circle. Nobody is making money. Everyone is pretending they will. There is only one solution to a bubble this big. The government. Three days after Trump's inauguration — Operation Stargate. $500 billion for AI data centers. Not because AI is profitable. Because the government needs the surveillance infrastructure that AI makes possible. AI needed the government to survive. The government needed AI to control. They found each other. And you are paying for it.

Predictive History

19,635 просмотров • 2 месяцев назад

Host: The White House, one of those places where you say, 'the stories these walls could tell if they could talk.' Well, some of those walls are now coming down. The facade of the East Wing is now being demolished as part of Trump's latest renovation plan to construct a $200 million ballroom.

Host: The White House, one of those places where you say, 'the stories these walls could tell if they could talk.' Well, some of those walls are now coming down. The facade of the East Wing is now being demolished as part of Trump's latest renovation plan to construct a $200 million ballroom.

FactPost

47,086 просмотров • 9 месяцев назад

Jeff Passan says Shohei Ohtani earns over $100 million a year off the field and helped the Dodgers become MLB’s first $1 billion revenue franchise “Personally, with all of the advertisements, sponsorships, and stuff like that, it’s upward of $100 million.” “The Los Angeles Dodgers are not the Los Angeles Dodgers—they are the Shohei Ohtani Shell Corporation.” “Good for them. They saw what the Angels never did.” “They understood that Ohtani himself is a monolith.” “They saw the international possibilities in Japan.” “They saw the business possibilities.” “It’s everything—the tours, the tourists, the merchandise, the sponsorships, the whole kit and caboodle.” “The Dodgers just last year became the first Major League Baseball franchise to have more than $1 billion in revenue in one year.” “And they’re going to do it again this year

Jeff Passan says Shohei Ohtani earns over $100 million a year off the field and helped the Dodgers become MLB’s first $1 billion revenue franchise “Personally, with all of the advertisements, sponsorships, and stuff like that, it’s upward of $100 million.” “The Los Angeles Dodgers are not the Los Angeles Dodgers—they are the Shohei Ohtani Shell Corporation.” “Good for them. They saw what the Angels never did.” “They understood that Ohtani himself is a monolith.” “They saw the international possibilities in Japan.” “They saw the business possibilities.” “It’s everything—the tours, the tourists, the merchandise, the sponsorships, the whole kit and caboodle.” “The Dodgers just last year became the first Major League Baseball franchise to have more than $1 billion in revenue in one year.” “And they’re going to do it again this year

Isaac Bassey

4,240,182 просмотров • 8 дней назад