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🚨🇺🇸🇨🇳 MICROSOFT & OPENAI SUSPECT DEEPSEEK OF “BORROWING” THEIR TECH Microsoft and OpenAI are investigating whether DeepSeek, a Chinese AI startup, helped itself to OpenAI’s data using its API. Microsoft’s security team flagged suspicious large-scale data extraction in late 2023, suggesting DeepSeek may have sneakily bypassed restrictions to grab...

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Mario Nawfal

3,631,451 subscribers

822,553 Aufrufe • vor 1 Jahr •via X (Twitter)

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9 Kommentare

Profilbild von John van Rijck
John van Rijckvor 1 Jahr

probably the other way around

Profilbild von Brian Basson
Brian Bassonvor 1 Jahr

wouldn't surprise me one bit, they're great at copy and paste....

Profilbild von Inverted Hedge
Inverted Hedgevor 1 Jahr

Really? Because OpenAI definitely didn't train its model on a bunch of copywrited material they didn't pay for either. And then had the main whistleblower for this knocked off and called a suicide under incredibly suspicious conditions. Nope, certainly not.

Profilbild von Block
Blockvor 1 Jahr

Not surprising

Profilbild von 🫗
🫗vor 1 Jahr

Fuck Sam Altman

Profilbild von KF.eth 🧱⟁
KF.eth 🧱⟁vor 1 Jahr

It’s not f*cking 8th place trophy. Go get it. It’s a competition. WTF is this attitude

Profilbild von Barefoot Pregnant
Barefoot Pregnantvor 1 Jahr

If DeepSeek did siphon off OpenAI’s tech, that’s a massive blow.

Profilbild von Phucky McFacerson
Phucky McFacersonvor 1 Jahr

It just makes you wonder if china can make a better AI by copying our companies and morphing it, why arent american AI companies doing the same thing? Or are they already? @syrcles

Profilbild von Make Men Great Again
Make Men Great Againvor 1 Jahr

China stealing U.S. tech? Shocker. This is why Trump pushed America First. keep our AI, our jobs, and our future out of CCP hands.

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Lex Fridman

1,154,226 Aufrufe • vor 1 Jahr

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Dr Ola Brown

83,460 Aufrufe • vor 1 Jahr

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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

92,971 Aufrufe • vor 1 Monat

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!
0:48

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!

Brian Roemmele

85,538 Aufrufe • vor 4 Monaten

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0:42

ELON: SOME AI IS NOT MAXIMALLY TRUTH SEEKING “A concern for all the major AI programs. You’ve got Google DeepMind, OpenAI and Microsoft as the two largest players, and Meta somewhere in there. The concern I have, and it may seem small but I think it’s actually a very big issue, is that they are not maximally truth seeking. They’re pandering to political correctness.” Source: AI and Marketing YT

Mario Nawfal

29,403 Aufrufe • vor 6 Monaten

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0:22

🚨 CHINA'S AI PRICE WAR IS BECOMING A NIGHTMARE FOR US AI COMPANIES. DeepSeek just made its 75% API price cut permanent. Days later, Xiaomi slashed its API costs by up to 99% to match it. The biggest threat to OpenAI and Anthropic was never another frontier model. It's developers realizing they can get competitive performance for a fraction of the cost. Now Chinese labs are turning AI into a commodity. Pricing it like electricity. Giving it away to WIN the market. The West is still selling AI like a premium product. China is selling it like electricity...

CryptoGoos

39,046 Aufrufe • vor 2 Monaten

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5:17

Elon Musk Elon Musk, who co-founded and invested in an open source, non-profit OpenAI ~$50 million: I AM THE REASON OpenAI EXISTS “I am the reason OpenAI exists... I used to be a close friend with Larry Page, and I was staying at his house, and we'd have these conversations long into the evening about AI, and I would be constantly urging him to be careful about the danger of AI. And he was really not concerned about the danger of AI and was quite cavalier about it. And at the time, Google, especially after the acquisition of DeepMind, had three-quarters of the world's AI talent; they had a lot of computers, a lot of money, so it was a unipolar world for AI. And we got a unipolar world, but the person who controls that does not, or at least did not seem to be concerned about AI safety. That sounded like a real problem. The final straw was Larry calling me a speciest for being a pro-human consciousness instead of machine consciousness, and I like, 'Well, yes, I guess I am a speciest.' I came up with the name [OpenAI], which refers to open source. The intent was to what is the opposite of Google, would be an open source non-profit, because Google is closed source profit, and that profit motivation could be dangerous... It does seem weird that something can be a nonprofit, open source, and somehow transform itself into a for-profit, closed source. I mean, this would be like, let's say you founded the organization to save the Amazon rainforest, but instead, they became a lumber company and chopped down the forest and sold it for money. And you'd be, therefore, like, 'Wait a second, that's the exact opposite of what I gave the money for. Is that legal?' That doesn't seem legal. And if, in general, it is legal to start a company as a non-profit and then take the IP and transfer it to a for-profit that then makes tons of money, shouldn't everyone start? Shouldn't that be the default? And I also think it is important to understand, like when push comes to shove, let's say they do create some digital super intelligence, almost Godlike intelligence, well, who is in control, and what is exactly the relationship between OpenAI and Microsoft? And I do worry that Microsoft actually may be more in control than the leadership team at OpenAI realizes. I mean, Microsoft, as part of Microsoft Investment, has rights to all of the software, all of the model weights, and everything necessary to run the inference system. At any point, Microsoft could cut off OpenAI.”

Eva Fo𝕏 🦊 Claudius Nero's Legion

527,742 Aufrufe • vor 7 Monaten

Cloudflare CEO Matthew Prince says Googlebot sees 3.2x more of the web than OpenAI, and 4.8x more than Microsoft. And he worries this advantage will allow Google to run away with the AI race, with no one else being able to catch them. "For every one page that OpenAI sees, Google is seeing 3.2." "What I worry about is, because Google has this unique access to the web that nobody else has, the game might just go to them. Because at the end of the day, whoever has the most data wins in the era of AI."
1:46

Cloudflare CEO Matthew Prince says Googlebot sees 3.2x more of the web than OpenAI, and 4.8x more than Microsoft. And he worries this advantage will allow Google to run away with the AI race, with no one else being able to catch them. "For every one page that OpenAI sees, Google is seeing 3.2." "What I worry about is, because Google has this unique access to the web that nobody else has, the game might just go to them. Because at the end of the day, whoever has the most data wins in the era of AI."

TBPN

164,015 Aufrufe • vor 7 Monaten

Cloudflare CEO Matthew Prince says Googlebot sees 3.2x more of the web than OpenAI, and 4.8x more than Microsoft. And he worries this advantage will allow Google to run away with the AI race, with no one else being able to catch them. "For every one page that OpenAI sees, Google is seeing 3.2." "What I worry about is, because Google has this unique access to the web that nobody else has, the game might just go to them. Because at the end of the day, whoever has the most data wins in the era of AI."
1:46

Cloudflare CEO Matthew Prince says Googlebot sees 3.2x more of the web than OpenAI, and 4.8x more than Microsoft. And he worries this advantage will allow Google to run away with the AI race, with no one else being able to catch them. "For every one page that OpenAI sees, Google is seeing 3.2." "What I worry about is, because Google has this unique access to the web that nobody else has, the game might just go to them. Because at the end of the day, whoever has the most data wins in the era of AI."

TBPN

98,466 Aufrufe • vor 6 Monaten

🚨🇺🇸 69 SECONDS | BIG TECH WAR ERUPTS OVER AI CODING TOOLS The AI coding assistant space just turned into a battlefield - and Windsurf is at the center. OpenAI made a $3B bid for the startup, but the deal imploded after Microsoft - with a $13B stake in OpenAI - demanded Windsurf’s tech for GitHub Copilot. Enter Google: they poached Windsurf’s CEO and 40 devs for $2.4B to power Gemini. Then rival Cognition swooped in, hiring 200 staff to boost its Devon product. It’s a high-stakes grab for the AI coding tools that could supercharge autonomous development - and decide who wins the tightening LLM race. presented by Buzz.eth
1:04

🚨🇺🇸 69 SECONDS | BIG TECH WAR ERUPTS OVER AI CODING TOOLS The AI coding assistant space just turned into a battlefield - and Windsurf is at the center. OpenAI made a $3B bid for the startup, but the deal imploded after Microsoft - with a $13B stake in OpenAI - demanded Windsurf’s tech for GitHub Copilot. Enter Google: they poached Windsurf’s CEO and 40 devs for $2.4B to power Gemini. Then rival Cognition swooped in, hiring 200 staff to boost its Devon product. It’s a high-stakes grab for the AI coding tools that could supercharge autonomous development - and decide who wins the tightening LLM race. presented by Buzz.eth

Mario Nawfal

116,633 Aufrufe • vor 1 Jahr

🇨🇳 🇺🇸 CHINA'S AI STACK IS GETTING DANGEROUSLY COMPETITIVE. Huawei's Ascend chips are now powering DeepSeek at a fraction of Western inference costs. The result: DeepSeek just made its 75% API price cut permanent on DeepSeek-V4-Pro. This is not a promotion. This is the new floor. The full vertical stack outside US sanctions and outside Nvidia's margins. DeepSeek can keep cutting. Chinese tech gets cheaper every quarter. A massive global undercut is no longer a question of if, only when. Western AI labs are running on $30,000 Nvidia chips at full markup. DeepSeek is running on Huawei silicon at cost. The unit economics aren't even in the same conversation. Every export ban that pushed China toward Huawei is paying off, for China.
0:22

🇨🇳 🇺🇸 CHINA'S AI STACK IS GETTING DANGEROUSLY COMPETITIVE. Huawei's Ascend chips are now powering DeepSeek at a fraction of Western inference costs. The result: DeepSeek just made its 75% API price cut permanent on DeepSeek-V4-Pro. This is not a promotion. This is the new floor. The full vertical stack outside US sanctions and outside Nvidia's margins. DeepSeek can keep cutting. Chinese tech gets cheaper every quarter. A massive global undercut is no longer a question of if, only when. Western AI labs are running on $30,000 Nvidia chips at full markup. DeepSeek is running on Huawei silicon at cost. The unit economics aren't even in the same conversation. Every export ban that pushed China toward Huawei is paying off, for China.

CryptoGoos

43,154 Aufrufe • vor 2 Monaten

China just made Silicon Valley's entire AI industry look like a scam. The US government spent 3 years trying to stop China from building competitive AI. But this backfired HORRIBLY. Here's what happened: Yesterday, a Chinese startup called DeepSeek released a new AI model called V4. It matches the performance of OpenAI and Anthropic's best models. At 1/7th the price. And for the first time ever, it was built on Chinese chips. NOT American ones. That last part is the one that terrifies the west. For context: Since 2022, the US has banned the export of advanced AI chips to China. The entire strategy was built on the assumption that if China can't access Nvidia's best hardware, they can't build frontier AI. But DeepSeek just proved that assumption wrong. Their V4 model was trained and runs on Huawei's Ascend chips. Huawei spent months working directly with DeepSeek to make sure V4 runs across their entire line of AI processors. Jensen Huang even predicted this on a recent podcast: "The day that DeepSeek comes out on Huawei first, that is a horrible outcome for our nation." That day was yesterday. And the numbers are crazy: DeepSeek V4 costs $3.48 per million output tokens. OpenAI's latest model GPT-5.5 costs $30. Anthropic's Claude charges $25. Same ballpark performance. 7x cheaper. Uber's CTO just admitted they burned through their ENTIRE 2026 AI budget in 4 months using Anthropic's tools. If Uber had used DeepSeek instead, that same budget would have lasted 7 YEARS. 4 months vs 7 years. Same work getting done. But the pricing isn't even the big thing here. The real story is what DeepSeek did with their technical report: They published the benchmarks where they LOSE. Every AI company cherry-picks the tests where their model wins. DeepSeek ran the full comparison against GPT-5.4 and Google's Gemini, found they trail frontier models by 3 to 6 months, and printed it anyway. They literally don't care because the price gap makes the performance gap irrelevant for 90% of use cases. So the US export controls didn't slow China down. They ACCELERATED China's independence. Because Chinese developers were FORCED to train models with limited resources, they had to figure out how to make AI radically more efficient. That constraint became their competitive advantage. Every generation of DeepSeek has gotten dramatically cheaper to train. V4 continues the trend. Meanwhile US companies are going the OPPOSITE direction: OpenAI's GPT-5.5 Pro costs $180 per million output tokens. That's 51x more expensive than DeepSeek V4 for comparable work. The Commerce Secretary confirmed this week that ZERO Nvidia advanced chip shipments have actually gone through to China despite being approved in January. So China built frontier AI anyway. Without American chips. At a fraction of the cost. And the market response tells you everything: Chinese chipmaker SMIC surged 10%. Huahong Semiconductor jumped 15%. DeepSeek's Chinese AI competitors Zhipu AI and MiniMax dropped 9% because V4 is destroying them too. DeepSeek is making Silicon Valley's pricing model look like a scam. US tech companies spent $650 billion on AI infrastructure this year. DeepSeek just showed the world you can match their output for pennies. The export controls were supposed to be America's ace card. Instead they taught China how to win without American chips, at American prices nobody can compete with. Jensen Huang was right. This is a horrible outcome. But it's the outcome America built for itself.
1:06

China just made Silicon Valley's entire AI industry look like a scam. The US government spent 3 years trying to stop China from building competitive AI. But this backfired HORRIBLY. Here's what happened: Yesterday, a Chinese startup called DeepSeek released a new AI model called V4. It matches the performance of OpenAI and Anthropic's best models. At 1/7th the price. And for the first time ever, it was built on Chinese chips. NOT American ones. That last part is the one that terrifies the west. For context: Since 2022, the US has banned the export of advanced AI chips to China. The entire strategy was built on the assumption that if China can't access Nvidia's best hardware, they can't build frontier AI. But DeepSeek just proved that assumption wrong. Their V4 model was trained and runs on Huawei's Ascend chips. Huawei spent months working directly with DeepSeek to make sure V4 runs across their entire line of AI processors. Jensen Huang even predicted this on a recent podcast: "The day that DeepSeek comes out on Huawei first, that is a horrible outcome for our nation." That day was yesterday. And the numbers are crazy: DeepSeek V4 costs $3.48 per million output tokens. OpenAI's latest model GPT-5.5 costs $30. Anthropic's Claude charges $25. Same ballpark performance. 7x cheaper. Uber's CTO just admitted they burned through their ENTIRE 2026 AI budget in 4 months using Anthropic's tools. If Uber had used DeepSeek instead, that same budget would have lasted 7 YEARS. 4 months vs 7 years. Same work getting done. But the pricing isn't even the big thing here. The real story is what DeepSeek did with their technical report: They published the benchmarks where they LOSE. Every AI company cherry-picks the tests where their model wins. DeepSeek ran the full comparison against GPT-5.4 and Google's Gemini, found they trail frontier models by 3 to 6 months, and printed it anyway. They literally don't care because the price gap makes the performance gap irrelevant for 90% of use cases. So the US export controls didn't slow China down. They ACCELERATED China's independence. Because Chinese developers were FORCED to train models with limited resources, they had to figure out how to make AI radically more efficient. That constraint became their competitive advantage. Every generation of DeepSeek has gotten dramatically cheaper to train. V4 continues the trend. Meanwhile US companies are going the OPPOSITE direction: OpenAI's GPT-5.5 Pro costs $180 per million output tokens. That's 51x more expensive than DeepSeek V4 for comparable work. The Commerce Secretary confirmed this week that ZERO Nvidia advanced chip shipments have actually gone through to China despite being approved in January. So China built frontier AI anyway. Without American chips. At a fraction of the cost. And the market response tells you everything: Chinese chipmaker SMIC surged 10%. Huahong Semiconductor jumped 15%. DeepSeek's Chinese AI competitors Zhipu AI and MiniMax dropped 9% because V4 is destroying them too. DeepSeek is making Silicon Valley's pricing model look like a scam. US tech companies spent $650 billion on AI infrastructure this year. DeepSeek just showed the world you can match their output for pennies. The export controls were supposed to be America's ace card. Instead they taught China how to win without American chips, at American prices nobody can compete with. Jensen Huang was right. This is a horrible outcome. But it's the outcome America built for itself.

Ricardo

280,891 Aufrufe • vor 3 Monaten

Microsoft is deceiving you by inflating its AI empire with money it handed its OWN customer first. They sold Wall Street a $37 billion AI business, then went silent the moment its own filing showed where that money came from. The line sits in the annual report for fiscal 2026: Microsoft recorded $24.1 billion of revenue from commercial arrangements with OpenAI, including revenue sharing payments. If you run that figure against Microsoft's own AI disclosures you'll find that OpenAI made up more than half, and likely around 70%, of everything the company counts as AI sales. ONE customer. A Microsoft spokesperson confirmed the figure covers all sales and revenue share from OpenAI. The 70% comes by assuming Microsoft's AI run rate kept growing at the 123% pace the company itself reported in March, which is the company's own optimistic math turned around on it. Now follow where that money starts: Microsoft has put around $12 billion into OpenAI since 2019. OpenAI spends its cash on computing power, and Microsoft is the cloud provider selling it. So the money leaves as an investment and comes back as an Azure bill. Microsoft then books that bill as AI revenue and shows it to investors as proof the AI business is "working." Microsoft invests in OpenAI -> OpenAI buys Microsoft compute -> Microsoft records the payment as AI revenue -> the AI growth story goes to Wall Street And a chunk of it never actually arrived. The same filing shows $6 billion of accounts receivable from OpenAI as of June 30. That is $6 billion of AI revenue Microsoft booked and had not been paid when the year closed. Now here's where it gets really concerning for anyone holding the stock... Microsoft has told the public how big its total AI business is exactly twice. Once for the quarter ending December 2024, when it said the unit was on pace for more than $13 billion a year. And once for the quarter ending March 2026, when Satya Nadella put it on pace for $37 billion. That $37 billion number went everywhere. It was the headline proof that Microsoft had won the AI race. Then fourth quarter earnings arrived, and Microsoft did NOT update it. The company that had been announcing the figure as its own scoreboard stopped announcing the figure. In the same stretch, the filing landed showing where most of it came from. So what is actually left underneath? The full year AI business ran near $34 billion. Take OpenAI out and roughly $10 billion remains. Microsoft has spent about $261 billion on capital expenditure since the start of 2022. That is the scale of the bet against what the rest of the AI business currently brings in. And the one customer holding it up is walking further away every quarter. In October, Microsoft's stake in OpenAI dropped to 27% from 32.5%. In April the partnership was rewritten so OpenAI can sell its products across any cloud it likes, which is how Amazon got a seat at the table. The exclusivity that made this arrangement valuable is gone. The compute bill and the unpaid $6 billion are still on Microsoft's books. Nadella spent two years telling the market Microsoft built the largest AI business in software. The filing shows one client bought most of it, on credit, using money Microsoft partly supplied. So watch the next earnings call: If Microsoft puts a fresh total AI number back on the board, the business found customers beyond OpenAI. If you hear a lot about AI momentum and never hear what it adds up to, you already know why the number went missing. But nonetheless, how is something like this even legal?
0:56

Microsoft is deceiving you by inflating its AI empire with money it handed its OWN customer first. They sold Wall Street a $37 billion AI business, then went silent the moment its own filing showed where that money came from. The line sits in the annual report for fiscal 2026: Microsoft recorded $24.1 billion of revenue from commercial arrangements with OpenAI, including revenue sharing payments. If you run that figure against Microsoft's own AI disclosures you'll find that OpenAI made up more than half, and likely around 70%, of everything the company counts as AI sales. ONE customer. A Microsoft spokesperson confirmed the figure covers all sales and revenue share from OpenAI. The 70% comes by assuming Microsoft's AI run rate kept growing at the 123% pace the company itself reported in March, which is the company's own optimistic math turned around on it. Now follow where that money starts: Microsoft has put around $12 billion into OpenAI since 2019. OpenAI spends its cash on computing power, and Microsoft is the cloud provider selling it. So the money leaves as an investment and comes back as an Azure bill. Microsoft then books that bill as AI revenue and shows it to investors as proof the AI business is "working." Microsoft invests in OpenAI -> OpenAI buys Microsoft compute -> Microsoft records the payment as AI revenue -> the AI growth story goes to Wall Street And a chunk of it never actually arrived. The same filing shows $6 billion of accounts receivable from OpenAI as of June 30. That is $6 billion of AI revenue Microsoft booked and had not been paid when the year closed. Now here's where it gets really concerning for anyone holding the stock... Microsoft has told the public how big its total AI business is exactly twice. Once for the quarter ending December 2024, when it said the unit was on pace for more than $13 billion a year. And once for the quarter ending March 2026, when Satya Nadella put it on pace for $37 billion. That $37 billion number went everywhere. It was the headline proof that Microsoft had won the AI race. Then fourth quarter earnings arrived, and Microsoft did NOT update it. The company that had been announcing the figure as its own scoreboard stopped announcing the figure. In the same stretch, the filing landed showing where most of it came from. So what is actually left underneath? The full year AI business ran near $34 billion. Take OpenAI out and roughly $10 billion remains. Microsoft has spent about $261 billion on capital expenditure since the start of 2022. That is the scale of the bet against what the rest of the AI business currently brings in. And the one customer holding it up is walking further away every quarter. In October, Microsoft's stake in OpenAI dropped to 27% from 32.5%. In April the partnership was rewritten so OpenAI can sell its products across any cloud it likes, which is how Amazon got a seat at the table. The exclusivity that made this arrangement valuable is gone. The compute bill and the unpaid $6 billion are still on Microsoft's books. Nadella spent two years telling the market Microsoft built the largest AI business in software. The filing shows one client bought most of it, on credit, using money Microsoft partly supplied. So watch the next earnings call: If Microsoft puts a fresh total AI number back on the board, the business found customers beyond OpenAI. If you hear a lot about AI momentum and never hear what it adds up to, you already know why the number went missing. But nonetheless, how is something like this even legal?

Ricardo

23,705 Aufrufe • vor 3 Tagen

What if the AI boom is not just a technology race, but a capital machine hiding in plain sight? The deeper I look at this ecosystem, the less it feels like a messy market and the more it looks like a closed financial loop. That is what makes this so striking. → Big Tech funds AI labs and infrastructure → AI labs and cloud players buy chips, GPUs, and networking → Model companies license capabilities back to the same giants funding the buildout What looks complicated is, in many ways, brutally simple. A money machine. And right now, that machine is being priced as if demand, revenue, and adoption will keep compounding with very little friction. That is the part I find most fascinating. Because the numbers are not just big. They are staggering. → Microsoft has invested more than $13B into OpenAI since 2019 → Oracle signed a $300B data centre capacity deal tied to OpenAI through 2029 → Meta is racing from roughly 150,000 NVIDIA GPUs in 2023 to around 1.3 million by the end of 2025 → Broadcom’s AI chip revenue is projected to jump from $3.8B in 2023 to $40B by 2026 What really stands out to me is how concentrated this loop has become. NVIDIA gets paid by nearly everyone. Infrastructure providers benefit early. AI companies are still betting on future monetization. Maybe it works. But that is the real question. Are we looking at durable economics, or one of the most elegantly circular bets the tech world has ever built? Do you think this AI capital loop is sustainable, or are we watching a beautifully engineered cycle that still has to prove itself? #AI #ArtificialIntelligence #OpenAI #NVIDIA #Microsoft #Infrastructure #DataCenters #Investing #BusinessStrategy #Innovation
2:32

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

Pascal Bornet

13,686 Aufrufe • vor 4 Monaten