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Bloomberg warns that China’s AI price war may make profitability difficult for years. They should be more worried about Wall Street. If the price war continues, the real casualty may not be AI. It may be the entire valuation structure built around it. OpenAI and Anthropic are valued as...

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13,830 Aufrufe • vor 9 Tagen •via X (Twitter)

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THIS IS A PERFECT EXAMPLE TO PROVE THE AI BUBBLE Claude AI developer Anthropic is valued at nearly $965B, while making only $20B in revenue. For comparison: Walmart is worth nearly the same amount ($940B), but makes $725B in revenue. Let that sink in. Same valuation range. Completely different economic reality. One is built on moving real goods through real infrastructure every day. The other is built on expectations of how widely AI will be used, and how profitable it will eventually become. And thats exactly where the big danger lies. Markets are no longer just pricing what companies earn. They are pricing what companies could become if everything goes right. And when valuations start converging like this, the uncomfortable question isn’t whether AI matters. It’s how much of that future has already been priced in.
0:31

THIS IS A PERFECT EXAMPLE TO PROVE THE AI BUBBLE Claude AI developer Anthropic is valued at nearly $965B, while making only $20B in revenue. For comparison: Walmart is worth nearly the same amount ($940B), but makes $725B in revenue. Let that sink in. Same valuation range. Completely different economic reality. One is built on moving real goods through real infrastructure every day. The other is built on expectations of how widely AI will be used, and how profitable it will eventually become. And thats exactly where the big danger lies. Markets are no longer just pricing what companies earn. They are pricing what companies could become if everything goes right. And when valuations start converging like this, the uncomfortable question isn’t whether AI matters. It’s how much of that future has already been priced in.

CryptoGoos

14,835 Aufrufe • vor 2 Monaten

China is trying to pop the US AI bubble. Xi just announced China will provide 30 countries with 5,000 AI training and seminar opportunities while building international AI application cooperation centers. China and the US have a different definition of "winning" the AI race. The US strategy: Spend trillions building and controlling the AI infrastructure the world will depend on through a proprietary ecosystem. China is taking the opposite approach: Build cheaper open-source models with similar performance and encourage the world to build on top of them. The bet is simple: The winner of AI will not necessarily be whoever owns the infrastructure. .... It will be whoever builds the best companies on top of it. Just like in the post-dot-com era... The biggest winners were companies like Amazon, Google, and Microsoft that built businesses on top of open infrastructure.
0:41

China is trying to pop the US AI bubble. Xi just announced China will provide 30 countries with 5,000 AI training and seminar opportunities while building international AI application cooperation centers. China and the US have a different definition of "winning" the AI race. The US strategy: Spend trillions building and controlling the AI infrastructure the world will depend on through a proprietary ecosystem. China is taking the opposite approach: Build cheaper open-source models with similar performance and encourage the world to build on top of them. The bet is simple: The winner of AI will not necessarily be whoever owns the infrastructure. .... It will be whoever builds the best companies on top of it. Just like in the post-dot-com era... The biggest winners were companies like Amazon, Google, and Microsoft that built businesses on top of open infrastructure.

Lukas Ekwueme

195,621 Aufrufe • vor 9 Tagen

🚨🇨🇳 China could crash the U.S. stock market Not with tariffs With AI MODEL DUMPING The same playbook they used in SOLAR and EVs Make it almost as good Sell it much cheaper Take the market Now they are doing it with AI Open models are getting close to U.S. frontier models But some run at just a fraction of the cost If a company can cut a $100M AI bill to a few million It will switch And that is the real problem OpenAI and Anthropic are not priced like normal companies They are priced like they have unlimited PRICING POWER China is trying to destroy that The AI BUBBLE was never about whether AI works It was about how much companies can charge for it
0:21

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

Leshka.eth ⛩

11,737 Aufrufe • vor 1 Monat

OPENAI JUST CUT MODEL PRICES AS THE AI PRICE WAR HEATS UP 🔥 OpenAI is cutting the price of Luna by 80% and Terra by 20%. It is also rolling out a faster mode that runs at twice the speed, but costs more. The bigger picture is clear -- cheaper Chinese models and tighter corporate AI budgets are forcing the biggest AI companies to compete on price, not just performance.
1:53

OPENAI JUST CUT MODEL PRICES AS THE AI PRICE WAR HEATS UP 🔥 OpenAI is cutting the price of Luna by 80% and Terra by 20%. It is also rolling out a faster mode that runs at twice the speed, but costs more. The bigger picture is clear -- cheaper Chinese models and tighter corporate AI budgets are forcing the biggest AI companies to compete on price, not just performance.

CryptosRus

12,382 Aufrufe • vor 13 Tagen

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?
1:05

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

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

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

Alex Mason 👁△

290,815 Aufrufe • vor 1 Monat

China impose Export Control on Rare Earth Trump raise tariff on Chinese goods for 100% Unless we have 🌮, we will have full blown trade war Will China continue to provide rare earth to TSMC? If not, where will Nvidia get GPU to sell? We maybe seeing the end of the AI bubble that support the outrageous valuation and the overextended stock market rally The pin that pops this bubble is here Be careful, this will make GFC look like child’s play Be prepared! ⚠️
0:39

China impose Export Control on Rare Earth Trump raise tariff on Chinese goods for 100% Unless we have 🌮, we will have full blown trade war Will China continue to provide rare earth to TSMC? If not, where will Nvidia get GPU to sell? We maybe seeing the end of the AI bubble that support the outrageous valuation and the overextended stock market rally The pin that pops this bubble is here Be careful, this will make GFC look like child’s play Be prepared! ⚠️

David Lee

89,447 Aufrufe • vor 10 Monaten

🚨 THIS IS HOW THE AI BUBBLE WILL BREAK THE S&P 500 Microsoft gave OpenAI $13B. OpenAI sent it back through Azure. Microsoft booked it as revenue. Google committed $40B to Anthropic. Anthropic agreed to send it back through Google Cloud and chips. They all call this loop “revenue.” Let's connect the dots: - Big Tech invests in the AI. - The AI buys Big Tech cloud. - Big Tech reports AI growth. - AI valuations explode. And Wall Street calls it demand. Ray Dalio warned that late-stage bubbles are driven by loops. That is what this looks like now. The technology is real. But the money is moving in circles. When holders finally ask how much of this “AI demand” is real, the bubble will burst. Reminder: I’ve called all the market tops and bottoms for the last 15 years, including the Bitcoin bottom at $16,000 and the top at $126,000. The next call will be even more important. When I exit the markets completely, I’ll post it here publicly like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.
0:34

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

WhaleTwits

52,506 Aufrufe • vor 1 Monat

Is AI really a bubble, or are we just early? Jeff Lutz 🔋 makes a good point: not every AI bet will work, but it’s hard to ignore what the biggest players are doing. NVIDIA, hyperscalers, Elon Musk and some of the world’s largest capital allocators are still spending billions to build more AI infrastructure. The hype will come and go. But if the spending keeps growing, maybe the more interesting question is: what do they see that the rest of the market doesn’t?
3:56

Is AI really a bubble, or are we just early? Jeff Lutz 🔋 makes a good point: not every AI bet will work, but it’s hard to ignore what the biggest players are doing. NVIDIA, hyperscalers, Elon Musk and some of the world’s largest capital allocators are still spending billions to build more AI infrastructure. The hype will come and go. But if the spending keeps growing, maybe the more interesting question is: what do they see that the rest of the market doesn’t?

Herbert Ong

22,497 Aufrufe • vor 1 Tag

🚨 SOMETHING VERY BAD IS HAPPENING The stock market keeps trying to push higher. OpenAI and Anthropic are now worth $2.1T. That is 10% of the entire Nasdaq. Look at the math: – $450B burned per year – $50B in actual revenue The entire AI bull case depends on one assumption: Inference gets cheaper. That is how funds justify the math. Spend massively today, scale later, margins explode when inference costs collapse. But that assumption is breaking: - Memory is getting expensive. - Compute is not getting cheap fast enough. - Inference is not falling the way everyone modeled. And if inference does not get dramatically cheaper, the whole AI margin story starts to crack. The loop is obvious: – Big players fund each other – Partnerships look perfect on paper – Revenue moves around inside the same system Everyone calls it growth. I call it the final stage of mania. In 2000, companies added “.com” to the name and valuations exploded: – Small profits – Massive valuations – Perfect stories Then reality hit. Nasdaq collapsed 80%. Now companies add “AI” to the name and reprice instantly: – Small profits – Massive valuations – Perfect AI stories This is the dot-com bubble with better AI branding. And bubbles do not warn you before they break. They break when everyone thinks the story is untouchable. The next move won’t wait for you. Follow and turn notifications on.
0:22

🚨 SOMETHING VERY BAD IS HAPPENING The stock market keeps trying to push higher. OpenAI and Anthropic are now worth $2.1T. That is 10% of the entire Nasdaq. Look at the math: – $450B burned per year – $50B in actual revenue The entire AI bull case depends on one assumption: Inference gets cheaper. That is how funds justify the math. Spend massively today, scale later, margins explode when inference costs collapse. But that assumption is breaking: - Memory is getting expensive. - Compute is not getting cheap fast enough. - Inference is not falling the way everyone modeled. And if inference does not get dramatically cheaper, the whole AI margin story starts to crack. The loop is obvious: – Big players fund each other – Partnerships look perfect on paper – Revenue moves around inside the same system Everyone calls it growth. I call it the final stage of mania. In 2000, companies added “.com” to the name and valuations exploded: – Small profits – Massive valuations – Perfect stories Then reality hit. Nasdaq collapsed 80%. Now companies add “AI” to the name and reprice instantly: – Small profits – Massive valuations – Perfect AI stories This is the dot-com bubble with better AI branding. And bubbles do not warn you before they break. They break when everyone thinks the story is untouchable. The next move won’t wait for you. Follow and turn notifications on.

Nonzee

921,069 Aufrufe • vor 2 Monaten

Nvidia put $420M into $TAO with 77% of it staked. Polychain added $200M on top of that. Grayscale and Bitwise both filed for spot TAO ETFs in the same quarter. The network generated $43M in real AI revenue last quarter from actual usage, not speculation. Most people are still treating this like a small cap gamble while institutions are treating it like infrastructure. The people who understand what is being built here will not need anyone to explain the price later.
5:52

Nvidia put $420M into $TAO with 77% of it staked. Polychain added $200M on top of that. Grayscale and Bitwise both filed for spot TAO ETFs in the same quarter. The network generated $43M in real AI revenue last quarter from actual usage, not speculation. Most people are still treating this like a small cap gamble while institutions are treating it like infrastructure. The people who understand what is being built here will not need anyone to explain the price later.

2xnmore

42,811 Aufrufe • vor 3 Monaten

🚨 SOMETHING VERY BAD IS HAPPENING The stock market keeps making new all-time highs. OpenAI and Anthropic are now worth $2.1T. That is 10% of the entire Nasdaq. Look at the math: – $450B burned per year – $50B in actual revenue The entire AI bull case depends on one assumption: Inference gets cheaper. That is how funds justify the math. Spend massively today, scale later, margins explode when inference costs collapse. But that assumption is breaking: - Memory is getting expensive. - Compute is not getting cheap fast enough. - Inference is not falling the way everyone modeled. And if inference does not get dramatically cheaper, the whole AI margin story starts to crack. The loop is obvious: – Big players fund each other – Partnerships look perfect on paper – Revenue moves around inside the same system Everyone calls it growth. I call it the final stage of mania. In 2000, companies added “.com” to the name and valuations exploded: – Small profits – Massive valuations – Perfect stories Then reality hit. Nasdaq collapsed 80%. Now companies add “AI” to the name and reprice instantly: – Small profits – Massive valuations – Perfect AI stories This is the dot-com bubble with better AI branding. And bubbles do not warn you before they break. They break when everyone thinks the story is untouchable. Turn notifications on. The next move won’t wait for you.
0:43

🚨 SOMETHING VERY BAD IS HAPPENING The stock market keeps making new all-time highs. OpenAI and Anthropic are now worth $2.1T. That is 10% of the entire Nasdaq. Look at the math: – $450B burned per year – $50B in actual revenue The entire AI bull case depends on one assumption: Inference gets cheaper. That is how funds justify the math. Spend massively today, scale later, margins explode when inference costs collapse. But that assumption is breaking: - Memory is getting expensive. - Compute is not getting cheap fast enough. - Inference is not falling the way everyone modeled. And if inference does not get dramatically cheaper, the whole AI margin story starts to crack. The loop is obvious: – Big players fund each other – Partnerships look perfect on paper – Revenue moves around inside the same system Everyone calls it growth. I call it the final stage of mania. In 2000, companies added “.com” to the name and valuations exploded: – Small profits – Massive valuations – Perfect stories Then reality hit. Nasdaq collapsed 80%. Now companies add “AI” to the name and reprice instantly: – Small profits – Massive valuations – Perfect AI stories This is the dot-com bubble with better AI branding. And bubbles do not warn you before they break. They break when everyone thinks the story is untouchable. Turn notifications on. The next move won’t wait for you.

Nonzee

160,648 Aufrufe • vor 3 Monaten

the IBM earnings reinforced something I think Wall Street is still underestimating: IBM is becoming an operating system for enterprise AI. The initial earnings reaction focused on the familiar metrics—revenue growth, infrastructure, margins and quarterly expectations. But that misses the bigger transformation underway. The AI market is bifurcating. On one side are companies building frontier models. On the other are companies helping enterprises operationalize AI—integrating it with existing systems and data, governing it, securing it, and turning AI into measurable business outcomes. IBM is increasingly positioning itself for that second market. And that's important because the enterprise AI conversation is moving from models to tools, from experimentation to outcomes, and ultimately toward autonomy and agents. IBM has decades of enterprise infrastructure, software, data and consulting relationships sitting underneath that transition. The mainframe isn't necessarily legacy in this world—it can become part of the context and transaction infrastructure AI acts upon. Wall Street initially looked at the quarter. I think the more important question is what IBM is becoming. My commentary below. #IBM #AI #EnterpriseAI #AgenticAI #HybridCloud
1:31

the IBM earnings reinforced something I think Wall Street is still underestimating: IBM is becoming an operating system for enterprise AI. The initial earnings reaction focused on the familiar metrics—revenue growth, infrastructure, margins and quarterly expectations. But that misses the bigger transformation underway. The AI market is bifurcating. On one side are companies building frontier models. On the other are companies helping enterprises operationalize AI—integrating it with existing systems and data, governing it, securing it, and turning AI into measurable business outcomes. IBM is increasingly positioning itself for that second market. And that's important because the enterprise AI conversation is moving from models to tools, from experimentation to outcomes, and ultimately toward autonomy and agents. IBM has decades of enterprise infrastructure, software, data and consulting relationships sitting underneath that transition. The mainframe isn't necessarily legacy in this world—it can become part of the context and transaction infrastructure AI acts upon. Wall Street initially looked at the quarter. I think the more important question is what IBM is becoming. My commentary below. #IBM #AI #EnterpriseAI #AgenticAI #HybridCloud

John Furrier

47,663 Aufrufe • vor 19 Tagen

China will crash the US stock market this year. They're dumping SOTA open-source models on the US, nearly as good as the frontier labs, basically free. Nobody can refuse cutting a $100M AI bill down to $5M. Once that deal is on the table for everyone, Anthropic and OpenAI can't justify their prices, or their valuations. The bubble isn't AI. It's the price of AI. And it's about to pop.
0:33

China will crash the US stock market this year. They're dumping SOTA open-source models on the US, nearly as good as the frontier labs, basically free. Nobody can refuse cutting a $100M AI bill down to $5M. Once that deal is on the table for everyone, Anthropic and OpenAI can't justify their prices, or their valuations. The bubble isn't AI. It's the price of AI. And it's about to pop.

Ben Cera

545,931 Aufrufe • vor 1 Monat

Jensen Huang says it has “largely conceded” China’s AI chip market to Huawei Nvidia was not rejected because China “hates” Nvidia. It was pushed out because Washington turned chips into a leash. China learned the lesson very clearly: You cannot build AI sovereignty on hardware that your geopolitical rival can revoke with one export-control memo. Jensen Huang can be friendly. Nvidia can be excellent. Chinese demand can be huge. None of that changes the strategic reality. If the neck of China’s AI industry depends on an American-controlled chip supply, then it is not an industry. It is a hostage. So China did what any serious civilization-state would do: It built alternatives. It endured the pain. It let Huawei grow into the space Washington forced open. Now Nvidia says it has “largely conceded” China’s AI chip market to Huawei. That is not China closing a door. That is America sawing off the bridge, then acting surprised when China built its own road.
2:06

Jensen Huang says it has “largely conceded” China’s AI chip market to Huawei Nvidia was not rejected because China “hates” Nvidia. It was pushed out because Washington turned chips into a leash. China learned the lesson very clearly: You cannot build AI sovereignty on hardware that your geopolitical rival can revoke with one export-control memo. Jensen Huang can be friendly. Nvidia can be excellent. Chinese demand can be huge. None of that changes the strategic reality. If the neck of China’s AI industry depends on an American-controlled chip supply, then it is not an industry. It is a hostage. So China did what any serious civilization-state would do: It built alternatives. It endured the pain. It let Huawei grow into the space Washington forced open. Now Nvidia says it has “largely conceded” China’s AI chip market to Huawei. That is not China closing a door. That is America sawing off the bridge, then acting surprised when China built its own road.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

235,419 Aufrufe • vor 2 Monaten

Will SaaS survive the AI era? Four reasons it may not: - Complexity: Software will be cheaper & easier to build yourself - Model Providers: Foundation model providers will move into the app layer. - Agentic Models: Models are becoming more agentic, they could handle tasks without extra SaaS layers. - Experience: SaaS today is built for human GUIs, AI in the future would not require any clicking. Link to the entire interview with Harry Stebbings below.
1:04

Will SaaS survive the AI era? Four reasons it may not: - Complexity: Software will be cheaper & easier to build yourself - Model Providers: Foundation model providers will move into the app layer. - Agentic Models: Models are becoming more agentic, they could handle tasks without extra SaaS layers. - Experience: SaaS today is built for human GUIs, AI in the future would not require any clicking. Link to the entire interview with Harry Stebbings below.

Turing

34,425 Aufrufe • vor 8 Monaten

This is the moment Chinese AI beat American AI. One of the largest public crypto companies in the world just DUMPED OpenAI and Anthropic. Coinbase switched to open-weight Chinese models from Zhipu and DeepSeek, and shaved nearly 50% off the company's internal AI spending. The numbers are absolutely ridiculous: Running the same enterprise workload through Anthropic's Claude costs $4,811. Running it through Zhipu's GLM 5.2 costs $544. That's a 9x price difference for equivalent output. OpenAI's GPT-5.5 sits in the middle at $3,357. DeepSeek's V4 lands at $1,071. Moonshot's Kimi at $948. On the actual benchmarks: Zhipu's GLM 5.2 scored 62.1 on SWE-bench Pro, the gold standard for coding. OpenAI's GPT-5.5 scored 58.6. One AI researcher called GLM 5.2 "at least as good as Opus 4.8 and GPT 5.5." Another called it "the first open model that can really compete with closed-source systems." The Chinese models are not just cheaper but they are now also beating American models on the benchmarks American companies pay $4,811 per workload for. Coinbase did the math first and reacted - more companies will certainly follow. Now watch what happens to the IPO timeline: Anthropic confidentially filed for an IPO targeting October at a $965 billion valuation. OpenAI followed days later with its own confidential filing. Both companies built their financial models on the assumption that they could keep charging enterprise prices that are 9 to 33x what Chinese competitors charge for the same task. Brian Armstrong publicly proved customers WILL leave. 45% of companies are now spending over $100,000 per month on AI, up from 20% last year. Every one of those customers is one quarterly budget review away from dumping American AI. OpenAI has reportedly already started preparing major token price cuts. Anthropic is expected to follow. And here's the thing... The export controls were supposed to CRUSH Chinese AI. The US government banned American AI chips, restricted model weights, blacklisted Alibaba and Baidu as Chinese military companies, and just banned Anthropic's flagship model from every foreign national on the planet. The entire premise of the American AI valuation bubble is that Washington can keep China two generations behind. But Chinese labs responded by building cheaper, more efficient models on inferior hardware and pricing them at one ninth the cost of the American alternative. And now American companies are voting with their checkbooks. The dominant American labs are valued at nearly $2 trillion combined on the assumption that their pricing power is durable. Coinbase proved it is not, and every customer doing a year-end budget review will be looking at the same math. For investors, the question here is what happens to the Anthropic IPO at $965 billion when the company is being forced to cut prices to defend share against open-weight Chinese models that score higher on the benchmarks. For everyone else, the bigger question is what happens when Washington spent four years and billions of dollars trying to contain Chinese AI, and the only thing that actually shifted in the end was American customers.
1:11

This is the moment Chinese AI beat American AI. One of the largest public crypto companies in the world just DUMPED OpenAI and Anthropic. Coinbase switched to open-weight Chinese models from Zhipu and DeepSeek, and shaved nearly 50% off the company's internal AI spending. The numbers are absolutely ridiculous: Running the same enterprise workload through Anthropic's Claude costs $4,811. Running it through Zhipu's GLM 5.2 costs $544. That's a 9x price difference for equivalent output. OpenAI's GPT-5.5 sits in the middle at $3,357. DeepSeek's V4 lands at $1,071. Moonshot's Kimi at $948. On the actual benchmarks: Zhipu's GLM 5.2 scored 62.1 on SWE-bench Pro, the gold standard for coding. OpenAI's GPT-5.5 scored 58.6. One AI researcher called GLM 5.2 "at least as good as Opus 4.8 and GPT 5.5." Another called it "the first open model that can really compete with closed-source systems." The Chinese models are not just cheaper but they are now also beating American models on the benchmarks American companies pay $4,811 per workload for. Coinbase did the math first and reacted - more companies will certainly follow. Now watch what happens to the IPO timeline: Anthropic confidentially filed for an IPO targeting October at a $965 billion valuation. OpenAI followed days later with its own confidential filing. Both companies built their financial models on the assumption that they could keep charging enterprise prices that are 9 to 33x what Chinese competitors charge for the same task. Brian Armstrong publicly proved customers WILL leave. 45% of companies are now spending over $100,000 per month on AI, up from 20% last year. Every one of those customers is one quarterly budget review away from dumping American AI. OpenAI has reportedly already started preparing major token price cuts. Anthropic is expected to follow. And here's the thing... The export controls were supposed to CRUSH Chinese AI. The US government banned American AI chips, restricted model weights, blacklisted Alibaba and Baidu as Chinese military companies, and just banned Anthropic's flagship model from every foreign national on the planet. The entire premise of the American AI valuation bubble is that Washington can keep China two generations behind. But Chinese labs responded by building cheaper, more efficient models on inferior hardware and pricing them at one ninth the cost of the American alternative. And now American companies are voting with their checkbooks. The dominant American labs are valued at nearly $2 trillion combined on the assumption that their pricing power is durable. Coinbase proved it is not, and every customer doing a year-end budget review will be looking at the same math. For investors, the question here is what happens to the Anthropic IPO at $965 billion when the company is being forced to cut prices to defend share against open-weight Chinese models that score higher on the benchmarks. For everyone else, the bigger question is what happens when Washington spent four years and billions of dollars trying to contain Chinese AI, and the only thing that actually shifted in the end was American customers.

Ricardo

252,183 Aufrufe • vor 1 Monat

AI doesn’t scale on mega-models — it scales on distilled skills at the edge. From Davos, Qualcomm's Nakul Duggal breaks down the real physics of edge AI: smaller, purpose-built models, mixed precision, and ruthless focus on power + cost efficiency. The biggest constraint is that if AI runs in robotics, ADAS, or edge automation, it has to be efficient. Watch the full conversation to see why edge AI outcomes depend on efficiency by design:
1:38

AI doesn’t scale on mega-models — it scales on distilled skills at the edge. From Davos, Qualcomm's Nakul Duggal breaks down the real physics of edge AI: smaller, purpose-built models, mixed precision, and ruthless focus on power + cost efficiency. The biggest constraint is that if AI runs in robotics, ADAS, or edge automation, it has to be efficient. Watch the full conversation to see why edge AI outcomes depend on efficiency by design:

Six Five Media

74,120 Aufrufe • vor 5 Monaten

In Ackman's latest interview he divides the AI market, stating that it is not a bubble at the foundational layer, but highly risky at the software/model layer. He sees "near infinite demand" for compute. He believes infrastructure providers such as Microsoft, Amazon, Meta, and even SpaceX will earn massive returns on their data center investments. He is highly skeptical of pure model layer businesses like OpenAI and Anthropic. He notes they face massive capital burn rates and an existential threat from open-source models such as Chinese model and SpaceX that are driving the cost of AI access effectively to zero. A business model reliant on charging for proprietary models will collapse if open-source alternatives are essentially free. $AMZN $META $MSFT $SPCX
3:09

In Ackman's latest interview he divides the AI market, stating that it is not a bubble at the foundational layer, but highly risky at the software/model layer. He sees "near infinite demand" for compute. He believes infrastructure providers such as Microsoft, Amazon, Meta, and even SpaceX will earn massive returns on their data center investments. He is highly skeptical of pure model layer businesses like OpenAI and Anthropic. He notes they face massive capital burn rates and an existential threat from open-source models such as Chinese model and SpaceX that are driving the cost of AI access effectively to zero. A business model reliant on charging for proprietary models will collapse if open-source alternatives are essentially free. $AMZN $META $MSFT $SPCX

CapexAndChill

137,444 Aufrufe • vor 29 Tagen

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA
1:48

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA

Karl Mehta

14,983 Aufrufe • vor 1 Monat