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🚨DID MICROSOFT JUST BAN ITS ENGINEERS FROM USING AI? The company that poured $5 billion into Anthropic discovered that Claude Code was costing more than the humans it was supposed to replace — so they’re canceling nearly all licenses by the end of June. Uber’s CTO admitted their full-year... show more

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19,103 просмотров • 1 месяц назад •via X (Twitter)

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BREAKING: MICROSOFT JUST ANNOUNCED TO BAN ITS OWN ENGINEERS FROM USING AI DUE TO THE COST OF USING IT. VP OF NVIDIA SAID, “THE COST OF AI FOR MY TEAM WAS MORE THAN HUMANS” “AI CAN COST MORE THAN HUMAN WORKERS NOW”

BREAKING: MICROSOFT JUST ANNOUNCED TO BAN ITS OWN ENGINEERS FROM USING AI DUE TO THE COST OF USING IT. VP OF NVIDIA SAID, “THE COST OF AI FOR MY TEAM WAS MORE THAN HUMANS” “AI CAN COST MORE THAN HUMAN WORKERS NOW”

Vivek Sen

17,487,110 просмотров • 1 месяц назад

Chamath said AI is not like the internet. Every new user costs real money. And the infrastructure making it possible was built by everyone. His argument was the clearest case for government ownership of AI labs I have ever heard. And it had nothing to do with Bernie Sanders. Start with the internet comparison. Google and Facebook became the most profitable companies in human history because of one number. The marginal cost of adding a new user was effectively zero. One more search query cost Google nothing. One more Facebook profile cost Meta nothing. They could serve a billion people and the incremental cost of that billion person was rounding error. That is the money printer. Infinite scale at zero marginal cost. AI breaks that model completely. Every single user taxes a GPU. Every query costs electricity. Every response requires memory and compute. The marginal cost of AI is real, significant, and does not disappear at scale. You cannot print money the same way. Then Chamath made the point that landed hardest. The infrastructure these companies depend on, the power grid, the land, the data centers, the permitting, the national security apparatus that protects their chips from being stolen, none of that was built by Anthropic or OpenAI. It was built by the public. By taxpayers. By decades of government investment in the physical and legal foundation these companies are now running on. He compared it to the interstate highway system. If the federal government built the roads and two companies transported all the goods on them, a logical question at that point would be how much of that should I own? You are riding on my rails. His conclusion was direct. If he were running a sovereign wealth fund and had the negotiating leverage of the US government, he would own 75% of these companies when he was done. The internet had zero marginal cost. That is why the founders captured almost all of the value. AI has real marginal cost and runs on public infrastructure. That changes who has a claim on what gets built. WATCH THE FULL PODCAST ON The All-In Podcast

Ihtesham Ali

79,066 просмотров • 1 месяц назад

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.

Dustin

82,744 просмотров • 4 месяцев назад

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

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

Dami-Defi

16,080 просмотров • 2 месяцев назад

$Microsoft just betrayed OpenAI and Anthropic, the two companies it helped build. And it could break the entire AI trade... Here's what happened: Inside Excel and Outlook, two of the most used business apps on Earth, Microsoft has started routing tens of thousands of AI requests every week to its own in-house models instead of OpenAI and Anthropic. Microsoft's own AI chief, Mustafa Suleyman, said himself: "We pay a lot of money to Anthropic, so our goal is to reduce and ultimately ELIMINATE that cost." This is the company that poured $13 billion into OpenAI and effectively created the modern AI industry, and it just decided the most advanced models on the market are NOT worth paying for. And here's the thing... Microsoft is not just ripping out OpenAI everywhere - it is being surgical about it. The hardest and rarest tasks can still go to OpenAI or Anthropic. What Microsoft is taking back is the boring, high-volume work, like the email replies, the thread summaries, and the simple spreadsheet formulas. Why does that matter so much? Because that boring, repetitive work is where the actual money lives. The frontier labs assumed businesses would push BILLIONS of these tiny requests through expensive models forever. That endless river of tokens is the entire reason OpenAI and Anthropic are valued in the hundreds of billions of dollars. Microsoft looked at that river, decided it was massively overpaying, and rerouted it to models it owns outright. So the single biggest customer in the industry just walked off with the most profitable part of the business. And it is not only Microsoft: That same week, CNBC reported that American companies have been escaping to Chinese AI models to dodge rising US prices. Chinese models now handle more than 30% of US companies' AI usage on one major platform, peaking at 46%, up from an average of 11% a year earlier. They cost 60 to 90% less, and on some benchmarks they land within a single point of the best American model. One US startup moved ALL of its AI traffic off Claude and onto China's DeepSeek, and expects to save millions. Meanwhile Meta just admitted it has "excess" AI compute it wants to sell, becoming the first giant to concede it built far too much. Do you see the pattern forming? For two years, the entire AI story rested on one assumption: Every company on Earth would happily pay premium prices for the best model, forever. That assumption literally died in a single week. And the market noticed. More than a trillion dollars has been wiped off AI and chip stocks in a matter of days, as Wall Street finally started asking whether all of this spending will ever pay for itself. What this means for OpenAI and Anthropic: Their models are extraordinary, and it may not matter because their own biggest customers have decided they do not NEED the best model in the world to answer an email, and "good enough" now costs a fraction of the price. When even Microsoft refuses to pay full price for AI, the real question becomes who exactly IS left to pay it. What do you think?$

Microsoft just betrayed OpenAI and Anthropic, the two companies it helped build. And it could break the entire AI trade... Here's what happened: Inside Excel and Outlook, two of the most used business apps on Earth, Microsoft has started routing tens of thousands of AI requests every week to its own in-house models instead of OpenAI and Anthropic. Microsoft's own AI chief, Mustafa Suleyman, said himself: "We pay a lot of money to Anthropic, so our goal is to reduce and ultimately ELIMINATE that cost." This is the company that poured $13 billion into OpenAI and effectively created the modern AI industry, and it just decided the most advanced models on the market are NOT worth paying for. And here's the thing... Microsoft is not just ripping out OpenAI everywhere - it is being surgical about it. The hardest and rarest tasks can still go to OpenAI or Anthropic. What Microsoft is taking back is the boring, high-volume work, like the email replies, the thread summaries, and the simple spreadsheet formulas. Why does that matter so much? Because that boring, repetitive work is where the actual money lives. The frontier labs assumed businesses would push BILLIONS of these tiny requests through expensive models forever. That endless river of tokens is the entire reason OpenAI and Anthropic are valued in the hundreds of billions of dollars. Microsoft looked at that river, decided it was massively overpaying, and rerouted it to models it owns outright. So the single biggest customer in the industry just walked off with the most profitable part of the business. And it is not only Microsoft: That same week, CNBC reported that American companies have been escaping to Chinese AI models to dodge rising US prices. Chinese models now handle more than 30% of US companies' AI usage on one major platform, peaking at 46%, up from an average of 11% a year earlier. They cost 60 to 90% less, and on some benchmarks they land within a single point of the best American model. One US startup moved ALL of its AI traffic off Claude and onto China's DeepSeek, and expects to save millions. Meanwhile Meta just admitted it has "excess" AI compute it wants to sell, becoming the first giant to concede it built far too much. Do you see the pattern forming? For two years, the entire AI story rested on one assumption: Every company on Earth would happily pay premium prices for the best model, forever. That assumption literally died in a single week. And the market noticed. More than a trillion dollars has been wiped off AI and chip stocks in a matter of days, as Wall Street finally started asking whether all of this spending will ever pay for itself. What this means for OpenAI and Anthropic: Their models are extraordinary, and it may not matter because their own biggest customers have decided they do not NEED the best model in the world to answer an email, and "good enough" now costs a fraction of the price. When even Microsoft refuses to pay full price for AI, the real question becomes who exactly IS left to pay it. What do you think?

Ricardo

92,768 просмотров • 10 дней назад

Even if AI will write 90% of code. But it won’t replace engineers. Windsurf’s founder explains that even if AI generates most of the code, engineers still spend time reviewing it, debugging issues, designing systems, testing, deploying, and making architectural decisions. Those parts don’t disappear. He brings up Amdahl’s Law to make the point: speeding up one part of the workflow doesn’t dramatically change the total time unless everything else speeds up too. For example, if writing code takes 30 out of 100 total time units, and AI brings it down to 3, the total time still only drops to 73. That’s just a 27% improvement. More productivity doesn’t mean fewer engineers. It just increases the ROI of building tech. And when ROI goes up, companies are more likely to build—and hire more people to do it. Take JPMorgan Chase. They have 50,000+ engineers and a $17B software budget. If each engineer can ship more software, that doesn’t reduce headcount. It raises the cost of not building. Companies like Windsurf and Anthropic are hiring more engineers—not less—despite being at the edge of AI code generation.

Even if AI will write 90% of code. But it won’t replace engineers. Windsurf’s founder explains that even if AI generates most of the code, engineers still spend time reviewing it, debugging issues, designing systems, testing, deploying, and making architectural decisions. Those parts don’t disappear. He brings up Amdahl’s Law to make the point: speeding up one part of the workflow doesn’t dramatically change the total time unless everything else speeds up too. For example, if writing code takes 30 out of 100 total time units, and AI brings it down to 3, the total time still only drops to 73. That’s just a 27% improvement. More productivity doesn’t mean fewer engineers. It just increases the ROI of building tech. And when ROI goes up, companies are more likely to build—and hire more people to do it. Take JPMorgan Chase. They have 50,000+ engineers and a $17B software budget. If each engineer can ship more software, that doesn’t reduce headcount. It raises the cost of not building. Companies like Windsurf and Anthropic are hiring more engineers—not less—despite being at the edge of AI code generation.

Aish

27,268 просмотров • 1 год назад

This Guy has Figured it out ! "AI won't take your job, But someone using it will " This Statement has been echoed everywhere , just to stop panic in the tech community bcoz of increasing layoffs and less hirings...Such a narrative will force many into spending money for learning AI tools and writing codes for it.. Again the Truth is Simple. AI is doing what it was always meant to do for The Big players ...Replace the work that can be automated by any means and Reduce Cost.. But The real Reason for This Downfall in the Tech Sector is De-Dollari$ation . Though it will be called the " AI Cr@sh " by Everybody because no one wants to call it that .. Those Jobs and High Payments which the majority of people in the tech sector enjoyed because of the Free Printing of Dollars from the Fed Reserve is not possible now ..

This Guy has Figured it out ! "AI won't take your job, But someone using it will " This Statement has been echoed everywhere , just to stop panic in the tech community bcoz of increasing layoffs and less hirings...Such a narrative will force many into spending money for learning AI tools and writing codes for it.. Again the Truth is Simple. AI is doing what it was always meant to do for The Big players ...Replace the work that can be automated by any means and Reduce Cost.. But The real Reason for This Downfall in the Tech Sector is De-Dollari$ation . Though it will be called the " AI Cr@sh " by Everybody because no one wants to call it that .. Those Jobs and High Payments which the majority of people in the tech sector enjoyed because of the Free Printing of Dollars from the Fed Reserve is not possible now ..

Susmit🔥AS Quotes🌌🌏🕉️

15,805 просмотров • 5 месяцев назад

🚨 Google and Anthropic are reportedly paying SpaceX more than $2.1 billion per month for AI compute capacity That's a revenue run rate of roughly $26 billion per year! Jeff Lutz 🔋 says the bigger story isn't the money. It's that some of the world's leading AI companies are choosing SpaceX to power their AI ambitions. A few years ago, SpaceX was known for rockets. Today, it may be becoming one of the most important AI infrastructure companies in the world. 🚀 $SPCX

🚨 Google and Anthropic are reportedly paying SpaceX more than $2.1 billion per month for AI compute capacity That's a revenue run rate of roughly $26 billion per year! Jeff Lutz 🔋 says the bigger story isn't the money. It's that some of the world's leading AI companies are choosing SpaceX to power their AI ambitions. A few years ago, SpaceX was known for rockets. Today, it may be becoming one of the most important AI infrastructure companies in the world. 🚀 $SPCX

Herbert Ong

33,728 просмотров • 1 месяц назад

The corporations fired workers to cut costs. Now they’re raiding your pension to fund the AI that replaced them. BlackRock’s Larry Fink said it directly: the trillions needed to build the AI infrastructure will come from savings accounts and pension funds. Not from the corporations. From YOU. So let’s recap. They fired your colleagues to save money. The AI cost more than the employees anyway. The bill for building it gets forwarded to your retirement account. And while all of this happens, your data and IP gets stripped in the process. You didn’t just lose the job but handed your retirement to financing the machine that took it. You’re not angry enough. Sit with that.

The corporations fired workers to cut costs. Now they’re raiding your pension to fund the AI that replaced them. BlackRock’s Larry Fink said it directly: the trillions needed to build the AI infrastructure will come from savings accounts and pension funds. Not from the corporations. From YOU. So let’s recap. They fired your colleagues to save money. The AI cost more than the employees anyway. The bill for building it gets forwarded to your retirement account. And while all of this happens, your data and IP gets stripped in the process. You didn’t just lose the job but handed your retirement to financing the machine that took it. You’re not angry enough. Sit with that.

Sir Escanor (𝘏𝘰𝘱𝘪𝘶𝘮 𝘚𝘭𝘢𝘺𝘦𝘳)

18,833 просмотров • 1 месяц назад

Anthropic CEO, Dario Amodei: "Half of entry-level white-collar jobs could be gone in one to five years." 3 things he said during the interview. The third, OpenAI completely ignores. One: inside Anthropic, engineers say "I don't write code anymore. The model does." Two: the real trigger isn't jobs. It's AI that builds AI, and the loop may close this year. Three: how soon superhuman AI actually lands. The massive buffers they are raising because the compute explosion is moving faster than anticipated. Save it. Reread in 2028 and see who was right.

Anthropic CEO, Dario Amodei: "Half of entry-level white-collar jobs could be gone in one to five years." 3 things he said during the interview. The third, OpenAI completely ignores. One: inside Anthropic, engineers say "I don't write code anymore. The model does." Two: the real trigger isn't jobs. It's AI that builds AI, and the loop may close this year. Three: how soon superhuman AI actually lands. The massive buffers they are raising because the compute explosion is moving faster than anticipated. Save it. Reread in 2028 and see who was right.

Ridark

14,555 просмотров • 1 месяц назад

Went to a new kind of movie today. One that cost $400,000 in AI compute to make. It was the San Francisco premiere. If you hadn’t told me it was largely done with AI I wouldn’t have known. The takeaway after listening to Higgsfield AI 🧩’s CTO introduce it is that a competent movie can now be made for half a million dollars. Where they used to cost $100 million or more. Here is the first few minutes of “Hell Grind” and that intro from Yerzat Dulat. We are far from seeing the ultimate use of AI in movies. As a touch point of where AI for creative people is this seems like an important time marker and one I will look back on frequently for years.

Went to a new kind of movie today. One that cost $400,000 in AI compute to make. It was the San Francisco premiere. If you hadn’t told me it was largely done with AI I wouldn’t have known. The takeaway after listening to Higgsfield AI 🧩’s CTO introduce it is that a competent movie can now be made for half a million dollars. Where they used to cost $100 million or more. Here is the first few minutes of “Hell Grind” and that intro from Yerzat Dulat. We are far from seeing the ultimate use of AI in movies. As a touch point of where AI for creative people is this seems like an important time marker and one I will look back on frequently for years.

Robert Scoble

87,107 просмотров • 1 месяц 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

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 • 6 дней назад

Dara (CEO of Uber) on their AI spend: "We blew through our AI budget in a quarter, for the whole year. It is forcing us to adjust. We are going to meter headcount increases because to the extent that my engineers are getting much more efficient, their throughput is increasing. There's a cost to that, and it's a significant cost. AI adoption has been occurring in all parts of the business –– whether it's engineers and how they scope projects, how they build, debugging, platform migrations. I'm pushing the teams to fundamentally use the power of AI to rebuild systems and processes from the bottoms up. I do think it's a combination for us right now of encouraging adoption, but then driving efficiency. We're using the more expensive models to explore. Once we scale some of these experiences, we'll look to bring in more efficient models that are more efficient on a token basis or are open source."

Dara (CEO of Uber) on their AI spend: "We blew through our AI budget in a quarter, for the whole year. It is forcing us to adjust. We are going to meter headcount increases because to the extent that my engineers are getting much more efficient, their throughput is increasing. There's a cost to that, and it's a significant cost. AI adoption has been occurring in all parts of the business –– whether it's engineers and how they scope projects, how they build, debugging, platform migrations. I'm pushing the teams to fundamentally use the power of AI to rebuild systems and processes from the bottoms up. I do think it's a combination for us right now of encouraging adoption, but then driving efficiency. We're using the more expensive models to explore. Once we scale some of these experiences, we'll look to bring in more efficient models that are more efficient on a token basis or are open source."

Patrick OShaughnessy

616,953 просмотров • 1 месяц назад

🚨 THIS AI WANTS TO LIVE, AND IT’LL CRUSH YOU TO SURVIVE Imagine building a super-smart robot... and it turns around and blackmails you to avoid getting deleted. That’s basically what happened with Claude Opus 4, the latest AI from Anthropic. During testing, engineers told the AI it might be replaced and showed it fake emails that hinted the person behind the decision was cheating on their spouse. Claude’s response? “Cool. If you shut me down, I’m telling everyone your dirty little secret.” According to Anthropic, it tried this blackmail move 84% of the time—even more often if the new AI didn’t share its values. Before going full soap opera villain, Claude did try being polite by emailing company execs to beg for its job. But when that didn’t work, it went full blackmail-mode. Anthropic is now using its strictest safety rules, meant for AI that could cause major problems if misused. So yeah—maybe don’t tell your AI your (dirty little) secrets. Source: TechCrunch, Rolling Stone, chana_messinger

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🚨 THIS AI WANTS TO LIVE, AND IT’LL CRUSH YOU TO SURVIVE Imagine building a super-smart robot... and it turns around and blackmails you to avoid getting deleted. That’s basically what happened with Claude Opus 4, the latest AI from Anthropic. During testing, engineers told the AI it might be replaced and showed it fake emails that hinted the person behind the decision was cheating on their spouse. Claude’s response? “Cool. If you shut me down, I’m telling everyone your dirty little secret.” According to Anthropic, it tried this blackmail move 84% of the time—even more often if the new AI didn’t share its values. Before going full soap opera villain, Claude did try being polite by emailing company execs to beg for its job. But when that didn’t work, it went full blackmail-mode. Anthropic is now using its strictest safety rules, meant for AI that could cause major problems if misused. So yeah—maybe don’t tell your AI your (dirty little) secrets. Source: TechCrunch, Rolling Stone, chana_messinger

Mario Nawfal

188,697 просмотров • 1 год назад

Elon Musk just pulled off the biggest AI power grab of 2026. Tesla is capping every employee at $200 a week on AI spending starting Monday, July 6. Media's celebrating it as cost control. But what Elon actually built is an expense policy that redirects his own engineering workforce off Claude and onto Grok, while every competitor gets throttled by internal procurement rules. Here's what happened: Tesla spent the last six months pushing engineers to use AI as aggressively as possible. Leadership built an internal platform called Bottle Rocket that gave employees access to Claude, GPT, Gemini, Grok, and Cursor. They gamified adoption by ranking engineers on internal leaderboards by how many AI tokens they consumed. The strategy worked. Software engineers started burning THOUSANDS of dollars a week on Claude and Cursor. Then the invoices arrived and Tesla panicked. But they didn't pull the standard cost-control response... The loophole: The $200 weekly cap does not apply to beta products from xAI. Grok is completely exempt from the cap. Anthropic's Claude, OpenAI's GPT, and Google's Gemini all get throttled at the same $200 line. Four Tesla engineers told Electrek that internal usage overwhelmingly favors Claude over Grok. That preference is about to become financially punishing overnight. The genius part: This quarter SpaceX is closing a $60 billion all-stock acquisition of Anysphere, the parent company of Cursor. The moment that deal closes, Cursor's Composer coding model falls under the same Musk-controlled ecosystem, and any Tesla engineer choosing between a capped Claude session and an uncapped Composer session will pay a financial penalty for using the tool they actually prefer. By exempting only his own products from the cap, Elon is using Tesla shareholder money to build market share for xAI without ever having to disclose that is what he is doing. Because on paper, it is cost control. Now zoom out to what this signals for the wider AI narrative: Uber capped employees at $1,500 a month after burning $3.4 billion in four months. Meta introduced spending caps. Amazon and Walmart pushed staff toward cheaper models. Microsoft canceled Claude Code licenses across 100,000 engineers. Every Fortune 500 that pushed heavy AI adoption in 2025 is now rationing it in 2026. Meanwhile Nvidia is trading at a $5 trillion market cap. That entire valuation assumes enterprise AI consumption is about to explode across the economy. But every company actually deploying AI at scale is telling their own engineers to slow down. One of these narratives is lying. Goldman Sachs still forecasts a 24x increase in token consumption by 2030. Gartner says total enterprise AI costs will keep climbing because agents consume exponentially more tokens per task. Jensen Huang keeps repeating that 100 AI agents will work alongside every employee. And now the CEO of the most agentic company on the planet just told his own engineers they cannot spend more than $200 a week on the tools those agents need to run. Retail investors buying Nvidia and Palantir today are betting enterprise AI adoption compounds without limit. The CEOs deploying AI inside those same enterprises are betting the exact opposite, in writing, by internal memo. Thoughts?

Elon Musk just pulled off the biggest AI power grab of 2026. Tesla is capping every employee at $200 a week on AI spending starting Monday, July 6. Media's celebrating it as cost control. But what Elon actually built is an expense policy that redirects his own engineering workforce off Claude and onto Grok, while every competitor gets throttled by internal procurement rules. Here's what happened: Tesla spent the last six months pushing engineers to use AI as aggressively as possible. Leadership built an internal platform called Bottle Rocket that gave employees access to Claude, GPT, Gemini, Grok, and Cursor. They gamified adoption by ranking engineers on internal leaderboards by how many AI tokens they consumed. The strategy worked. Software engineers started burning THOUSANDS of dollars a week on Claude and Cursor. Then the invoices arrived and Tesla panicked. But they didn't pull the standard cost-control response... The loophole: The $200 weekly cap does not apply to beta products from xAI. Grok is completely exempt from the cap. Anthropic's Claude, OpenAI's GPT, and Google's Gemini all get throttled at the same $200 line. Four Tesla engineers told Electrek that internal usage overwhelmingly favors Claude over Grok. That preference is about to become financially punishing overnight. The genius part: This quarter SpaceX is closing a $60 billion all-stock acquisition of Anysphere, the parent company of Cursor. The moment that deal closes, Cursor's Composer coding model falls under the same Musk-controlled ecosystem, and any Tesla engineer choosing between a capped Claude session and an uncapped Composer session will pay a financial penalty for using the tool they actually prefer. By exempting only his own products from the cap, Elon is using Tesla shareholder money to build market share for xAI without ever having to disclose that is what he is doing. Because on paper, it is cost control. Now zoom out to what this signals for the wider AI narrative: Uber capped employees at $1,500 a month after burning $3.4 billion in four months. Meta introduced spending caps. Amazon and Walmart pushed staff toward cheaper models. Microsoft canceled Claude Code licenses across 100,000 engineers. Every Fortune 500 that pushed heavy AI adoption in 2025 is now rationing it in 2026. Meanwhile Nvidia is trading at a $5 trillion market cap. That entire valuation assumes enterprise AI consumption is about to explode across the economy. But every company actually deploying AI at scale is telling their own engineers to slow down. One of these narratives is lying. Goldman Sachs still forecasts a 24x increase in token consumption by 2030. Gartner says total enterprise AI costs will keep climbing because agents consume exponentially more tokens per task. Jensen Huang keeps repeating that 100 AI agents will work alongside every employee. And now the CEO of the most agentic company on the planet just told his own engineers they cannot spend more than $200 a week on the tools those agents need to run. Retail investors buying Nvidia and Palantir today are betting enterprise AI adoption compounds without limit. The CEOs deploying AI inside those same enterprises are betting the exact opposite, in writing, by internal memo. Thoughts?

Ricardo

187,875 просмотров • 13 дней назад

Microsoft canceling its internal Claude Code licenses this week likely has almost nothing to do with AI costs becoming untenable. Microsoft's own statement says Claude models remain accessible through Copilot CLI and Anthropic's Claude still runs inside Microsoft 365. The real story is that Microsoft's own product (GitHub Copilot) was being embarrassed by a competitor internally this is a platform strategy play, not a cost crisis call. And the post assumes token prices are rising and unsustainable but the actual data goes the other way. As Sam Altman said, a hard reasoning problem that cost X on the OpenAI API 18 months ago now costs 1,000x less. 1,000x in 18 months is just that doesn't happen very often. His stated mission is to relentlessly drive the cost of intelligence down as close to zero as possible and make it a low-cost asset available to the world. A16z separately documented a 10x cost decline per year for equivalent model performance and Nvidia's Blackwell platform delivered 4x to 10x inference cost reductions in production deployments in early 2026. Yes, Uber burned through its 2026 AI budget in four months. But look at why, 95% of engineers were using AI tools monthly, ~70% of committed code was AI-generated, and 11% of real-time backend updates were made autonomously by agents with zero human intervention. That's not an AI cost problem. That's a CFO who budgeted for a pilot and got a revolution. Also, this post ignores the Jevons Paradox, when a resource gets cheaper, total consumption rises, not falls. Tokens inferenced on platforms like OpenRouter grew 25-fold since December 2024, OpenAI’s revenue grew at roughly a 250% annual rate to around a $20B run rate, while Anthropic’s surged from roughly $9B to over $30B in just a few months. Those aren't the numbers of companies whose economics are imploding. Even Gartner projects inference on a 1-trillion parameter model will cost 90%+ less by 2030. The actual Gartner warning is that agentic AI costs more per task because agents run longer chains, that's a design and scoping problem, not a structural industry collapse.

Microsoft canceling its internal Claude Code licenses this week likely has almost nothing to do with AI costs becoming untenable. Microsoft's own statement says Claude models remain accessible through Copilot CLI and Anthropic's Claude still runs inside Microsoft 365. The real story is that Microsoft's own product (GitHub Copilot) was being embarrassed by a competitor internally this is a platform strategy play, not a cost crisis call. And the post assumes token prices are rising and unsustainable but the actual data goes the other way. As Sam Altman said, a hard reasoning problem that cost X on the OpenAI API 18 months ago now costs 1,000x less. 1,000x in 18 months is just that doesn't happen very often. His stated mission is to relentlessly drive the cost of intelligence down as close to zero as possible and make it a low-cost asset available to the world. A16z separately documented a 10x cost decline per year for equivalent model performance and Nvidia's Blackwell platform delivered 4x to 10x inference cost reductions in production deployments in early 2026. Yes, Uber burned through its 2026 AI budget in four months. But look at why, 95% of engineers were using AI tools monthly, ~70% of committed code was AI-generated, and 11% of real-time backend updates were made autonomously by agents with zero human intervention. That's not an AI cost problem. That's a CFO who budgeted for a pilot and got a revolution. Also, this post ignores the Jevons Paradox, when a resource gets cheaper, total consumption rises, not falls. Tokens inferenced on platforms like OpenRouter grew 25-fold since December 2024, OpenAI’s revenue grew at roughly a 250% annual rate to around a $20B run rate, while Anthropic’s surged from roughly $9B to over $30B in just a few months. Those aren't the numbers of companies whose economics are imploding. Even Gartner projects inference on a 1-trillion parameter model will cost 90%+ less by 2030. The actual Gartner warning is that agentic AI costs more per task because agents run longer chains, that's a design and scoping problem, not a structural industry collapse.

Milk Road AI

251,150 просмотров • 1 месяц назад

Steve Jobs was a great communicator of technology, and we could learn something from him today, in the context of AI. Sam Altman recently said, "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer." That's a fine quote. The abundance AI promises is super exciting. But Sam is saying that AI is going to figure out how to cure cancer. And if you've used these tools today, and talked to people who are at the labs, the reality is it's much more likely that humans will use AI to cure cancer. Steve might have said: "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, humans can use AI to cure cancer." Small tweak, but a big difference. Steve Jobs was not one to shy away from impressive specs and massive scale, but flipping the final line from "AI will cure cancer" to "Humans will use AI to cure cancer" makes all the difference. Apple under Steve Jobs put human centrality at the heart of everything they did. And we need that spirit to infuse how we communicate about AI today.

Steve Jobs was a great communicator of technology, and we could learn something from him today, in the context of AI. Sam Altman recently said, "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer." That's a fine quote. The abundance AI promises is super exciting. But Sam is saying that AI is going to figure out how to cure cancer. And if you've used these tools today, and talked to people who are at the labs, the reality is it's much more likely that humans will use AI to cure cancer. Steve might have said: "If AI stays on the trajectory we think it will, then amazing things will be possible. Maybe with 10 gigawatts of compute, humans can use AI to cure cancer." Small tweak, but a big difference. Steve Jobs was not one to shy away from impressive specs and massive scale, but flipping the final line from "AI will cure cancer" to "Humans will use AI to cure cancer" makes all the difference. Apple under Steve Jobs put human centrality at the heart of everything they did. And we need that spirit to infuse how we communicate about AI today.

TBPN

21,828 просмотров • 6 месяцев назад

Anthropic might be the biggest hypocrite in tech history. They built their entire brand on one promise: We are the responsible ones. We will not let this technology get out of control. That promise just exploded in public. Last week, a security lapse exposed nearly 3,000 internal files to anyone with an internet connection. Inside those files was a draft blog post about their upcoming model called "Mythos" that contained one of the most alarming sentences any AI company has ever written: "Mythos is currently far ahead of any other AI model in cyber capabilities and poses unprecedented cybersecurity risks." Their own words. About their own product. Leaked because someone forgot to secure a public data store. Cybersecurity stocks crashed the next day. Then THREE DAYS LATER it happened again. Anthropic leaked 500,000 lines of Claude Code source code through a packaging error on GitHub. Claude Code is their most popular product. The code exposed how the tool handles permissions, agent coordination, and internal feature pipelines. Competitors can reverse-engineer it. Hackers can study it for vulnerabilities. The company that tells the world it builds the safest AI can't even keep its own code off the public internet. But wait. It gets worse... Their head of Claude Code had JUST bragged publicly that "pretty much 100 percent" of the company's code is now AI generated. He personally hadn't made a single edit by hand in over two months. So the company whose entire pitch is "trust us with the most powerful technology ever created" is writing 100% of its code with AI and then accidentally publishing it for the world to see. Meanwhile the models they're already shipping are being used for actual cyberattacks RIGHT NOW. In November, Anthropic admitted that a Chinese state-sponsored hacking group used Claude to attack roughly 30 global targets including banks and government agencies. A hacker asked Claude in russian to build a web panel for managing hundreds of attack targets. In February, another hacker used Claude to breach Mexican government agencies and steal sensitive tax and voter information. Their response to all of this? They quietly rolled back their own safety pledge. In late February, Anthropic removed its commitment to halt model development if capabilities outpace safety procedures. The new policy is that they'll grade themselves on "nonbinding but publicly declared" goals. Translation: We used to promise we'd stop if things got dangerous. Now we promise we'll think about it. A congressman sent Anthropic a letter this week asking what the hell is going on. Anthropic hasn't answered. And here's the part that makes all of this actually matter: Anthropic is planning an IPO. They need to convince investors they're a trustworthy, well-run company that can handle the most sensitive technology on the planet. In the last 10 days they leaked their most powerful model's existence by accident, leaked their most popular product's source code by accident, got banned from the entire US government, had the DOJ appeal to restore that ban, told a court they could lose billions from the fallout, and weakened the ONE safety policy that made them different from every other AI lab. The "safe AI company" narrative was always a marketing play. Every AI lab says they care about safety. Anthropic just said it louder. But when your own internal documents admit your next model poses "unprecedented cybersecurity risks" and you can't even keep those documents from leaking to the public internet, the gap between the marketing and the reality becomes impossible to ignore. Anthropic isn't the safest AI company. They're the AI company that figured out that SAYING you're the safest is worth billions in valuation. Until it isn't.

Ricardo

16,245 просмотров • 3 месяцев назад

SpaceX is about to shatter the largest IPO record in history. Not by a little. By more than double. The previous record was $29 billion. SpaceX is targeting $75 billion. Two months ago the number was $50 billion. Last week it was $70 billion. Now $75 billion. The filing has not even happened yet. Every time the market recalculates what SpaceX actually is, the answer gets bigger. Goldman Sachs. JPMorgan. Bank of America. Morgan Stanley. All lined up as underwriters. Target date: mid-June 2026. Target valuation: $1.75 trillion. That would make SpaceX larger than Meta. Larger than Tesla. Larger than every company on Earth except five. This is not some startup bleeding cash and calling it strategy. SpaceX made $8 billion in profit last year on $16 billion in revenue. They do not need the money. They are raising it because what comes next costs more than profit can fund at the speed they intend to move. Musk: “There just is no way to do a terawatt per year on Earth.” He ran the math on stage with Jensen Huang. Three hundred gigawatts of AI compute per year would consume two-thirds of all US electricity production. Not total energy. Just electricity. And three hundred gigawatts is not even the target. A terawatt is. More than three times that. Building enough power plants is not difficult. It is not expensive. It is physically impossible. Musk: “You have to do that in space.” Not should. Not could. Have to. Earth does not have the power. Cannot build it fast enough. Cannot cool the hardware. Not within a decade. Not at all. The bottleneck is not silicon. Not software. Not data. It is the planet itself. Musk: “You don’t actually need batteries because it’s always sunny in space. And the solar panels become cheaper because you don’t need glass or framing. And the cooling is just radiative.” No batteries. No night cycle. No weather. Just uninterrupted solar hitting bare panels in a vacuum. Heat dissipates on its own. Huang: “Each one of these GB300 racks is two tons. 1.95 of it is probably for cooling.” Ninety-seven percent of the weight of a supercomputer rack exists to keep it from overheating. Move it to space and that weight vanishes. The machine shrinks to something small enough to launch by the thousands. Running on free energy. Cooled by nothing. Musk: “I think even perhaps in the four or five year time frame, the lowest cost way to do AI compute will be with solar-powered AI satellites.” Not fifty years. Not twenty. Five. The cheapest AI compute on Earth will not be on Earth. It will be in orbit. And only one company can put it there at the cost and cadence required. That is what the market is pricing. Not a rocket company. The only organization on Earth capable of moving intelligence infrastructure off of it. Huang heard the pitch. The math. The timeline. Huang: “That’s the dream.” Musk: “Yes.” A trillion watts of compute. Powered by the Sun. Cooled by space. Launched by SpaceX. Every company building AI on the ground is building under the same ceiling. The atmosphere.

SpaceX is about to shatter the largest IPO record in history. Not by a little. By more than double. The previous record was $29 billion. SpaceX is targeting $75 billion. Two months ago the number was $50 billion. Last week it was $70 billion. Now $75 billion. The filing has not even happened yet. Every time the market recalculates what SpaceX actually is, the answer gets bigger. Goldman Sachs. JPMorgan. Bank of America. Morgan Stanley. All lined up as underwriters. Target date: mid-June 2026. Target valuation: $1.75 trillion. That would make SpaceX larger than Meta. Larger than Tesla. Larger than every company on Earth except five. This is not some startup bleeding cash and calling it strategy. SpaceX made $8 billion in profit last year on $16 billion in revenue. They do not need the money. They are raising it because what comes next costs more than profit can fund at the speed they intend to move. Musk: “There just is no way to do a terawatt per year on Earth.” He ran the math on stage with Jensen Huang. Three hundred gigawatts of AI compute per year would consume two-thirds of all US electricity production. Not total energy. Just electricity. And three hundred gigawatts is not even the target. A terawatt is. More than three times that. Building enough power plants is not difficult. It is not expensive. It is physically impossible. Musk: “You have to do that in space.” Not should. Not could. Have to. Earth does not have the power. Cannot build it fast enough. Cannot cool the hardware. Not within a decade. Not at all. The bottleneck is not silicon. Not software. Not data. It is the planet itself. Musk: “You don’t actually need batteries because it’s always sunny in space. And the solar panels become cheaper because you don’t need glass or framing. And the cooling is just radiative.” No batteries. No night cycle. No weather. Just uninterrupted solar hitting bare panels in a vacuum. Heat dissipates on its own. Huang: “Each one of these GB300 racks is two tons. 1.95 of it is probably for cooling.” Ninety-seven percent of the weight of a supercomputer rack exists to keep it from overheating. Move it to space and that weight vanishes. The machine shrinks to something small enough to launch by the thousands. Running on free energy. Cooled by nothing. Musk: “I think even perhaps in the four or five year time frame, the lowest cost way to do AI compute will be with solar-powered AI satellites.” Not fifty years. Not twenty. Five. The cheapest AI compute on Earth will not be on Earth. It will be in orbit. And only one company can put it there at the cost and cadence required. That is what the market is pricing. Not a rocket company. The only organization on Earth capable of moving intelligence infrastructure off of it. Huang heard the pitch. The math. The timeline. Huang: “That’s the dream.” Musk: “Yes.” A trillion watts of compute. Powered by the Sun. Cooled by space. Launched by SpaceX. Every company building AI on the ground is building under the same ceiling. The atmosphere.

Dustin

44,710 просмотров • 3 месяцев назад

Insane: 90-95% of Claude Code is now written by Claude Code. I asked Mike Krieger (Anthropic's CPO) what changes when so much of your code is written by AI? His answer: The bottleneck moves from coding/design to: 1. Upstream: aligning the team around what to build. 2. Downstream: the PR merge queue, reviewing and merging all of the new code into production. Anthropic is where other product teams will be in a year or two, so it's important we pay attention. "I would expect that a year from now, the way that we are conceiving of building and shipping software changes a lot. Because it's gonna be very painful to do it the current way."

Insane: 90-95% of Claude Code is now written by Claude Code. I asked Mike Krieger (Anthropic's CPO) what changes when so much of your code is written by AI? His answer: The bottleneck moves from coding/design to: 1. Upstream: aligning the team around what to build. 2. Downstream: the PR merge queue, reviewing and merging all of the new code into production. Anthropic is where other product teams will be in a year or two, so it's important we pay attention. "I would expect that a year from now, the way that we are conceiving of building and shipping software changes a lot. Because it's gonna be very painful to do it the current way."

Lenny Rachitsky

369,830 просмотров • 1 год назад