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SITUATION EXPLAINED: What does the Chinese AI ecosystem actually look like beyond DeepSeek? Gabrierl (.Gabriel) asked FleetingBits, anonymous AI researcher. "Most people are familiar with DeepSeek. But if we look at other Chinese labs like Zhipu, Minimax, Moonshot, ByteDance, they're a little bit less well known." "Zhipu is sort...

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170,881 views • 1 month ago •via X (Twitter)

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The American AI company AfterQuery AfterQuery is reportedly generating at least $50 MILLION in recurring revenue from Chinese AI labs while maintaining ties to Ant Group Ant Group and Alibaba, two major Chinese technology companies. Its CEO Spencer Mateega publicly celebrated Moonshot AI’s Kimi model for topping an AfterQuery benchmark and called the Chinese team “cracked.”Moonshot AI is a Chinese AI company based in Beijing, China American AI executives are traveling to China, hiring China engagement managers and openly praising the Chinese models competing to overtake the United States in AI dominance. How many warning signs does Washington need before it stops American AI companies from helping China overtake the United States in the AI race? David Sacks
1:20

The American AI company AfterQuery AfterQuery is reportedly generating at least $50 MILLION in recurring revenue from Chinese AI labs while maintaining ties to Ant Group Ant Group and Alibaba, two major Chinese technology companies. Its CEO Spencer Mateega publicly celebrated Moonshot AI’s Kimi model for topping an AfterQuery benchmark and called the Chinese team “cracked.”Moonshot AI is a Chinese AI company based in Beijing, China American AI executives are traveling to China, hiring China engagement managers and openly praising the Chinese models competing to overtake the United States in AI dominance. How many warning signs does Washington need before it stops American AI companies from helping China overtake the United States in the AI race? David Sacks

Laura Loomer

47,849 views • 13 hours ago

China is once again unsettling its American competitors in the AI race. Chinese labs have returned to the spotlight with the unveiling of GLM 5.2, described as the most powerful AI model ever trained in China — and one of the leading open‑source models worldwide. 🔍 Key highlights of “GLM 5.2”: ♦️ It is considered the strongest AI model developed in China to date, and ranks among the smartest open‑source models available. ♦️ It operates at a cost less than one‑tenth that of Anthropic’s latest models, making it a far more economical option. ♦️ It is likely to attract developers and companies seeking powerful, low‑cost models — especially amid growing technical and geopolitical restrictions. ♦️ Some evaluations place the model among the top globally, trailing OpenAI’s models while outperforming several competitors in specialized benchmarks and performance tests.
0:42

China is once again unsettling its American competitors in the AI race. Chinese labs have returned to the spotlight with the unveiling of GLM 5.2, described as the most powerful AI model ever trained in China — and one of the leading open‑source models worldwide. 🔍 Key highlights of “GLM 5.2”: ♦️ It is considered the strongest AI model developed in China to date, and ranks among the smartest open‑source models available. ♦️ It operates at a cost less than one‑tenth that of Anthropic’s latest models, making it a far more economical option. ♦️ It is likely to attract developers and companies seeking powerful, low‑cost models — especially amid growing technical and geopolitical restrictions. ♦️ Some evaluations place the model among the top globally, trailing OpenAI’s models while outperforming several competitors in specialized benchmarks and performance tests.

China pulse 🇨🇳

14,293 views • 1 month ago

SITUATION EXPLAINED: American AI labs are worth ~$1T each. Chinese AI labs are worth tens of billions. What explains the gap? • Moonshot AI (Kimi) raising $2B at $30B, its third financing in six months • OpenAI and Anthropic: both around $1T • DeepSeek and Moonshot: tens of billions... one to two orders of magnitude smaller • DeepSeek rumored at ~$200M ARR • Chinese models don't compete on capability, they compete on price Theo Jaffee: "Markets are probably pricing in OpenAI and Anthropic kicking off recursive self-improvement first. The niche of DeepSeek and Moonshot is not that they're better... it's that they're much, much cheaper. Which is good for enterprise applications. But it's not as good for kicking off the singularity."
1:55

SITUATION EXPLAINED: American AI labs are worth ~$1T each. Chinese AI labs are worth tens of billions. What explains the gap? • Moonshot AI (Kimi) raising $2B at $30B, its third financing in six months • OpenAI and Anthropic: both around $1T • DeepSeek and Moonshot: tens of billions... one to two orders of magnitude smaller • DeepSeek rumored at ~$200M ARR • Chinese models don't compete on capability, they compete on price Theo Jaffee: "Markets are probably pricing in OpenAI and Anthropic kicking off recursive self-improvement first. The niche of DeepSeek and Moonshot is not that they're better... it's that they're much, much cheaper. Which is good for enterprise applications. But it's not as good for kicking off the singularity."

MTS

11,559 views • 2 months ago

Elon Musk explains how data centers in Space could help the US compete with China in AI “Given that Chinese AI companies are doing as well as they are with a relatively small amount of compute, it seems that if they had a lot of compute, there’s a good chance they would be the leaders. The constraints on AI are essentially electricity and AI chips. China is very strong in digital AI, and it has far more electricity than the United States. In fact, China already has more electricity than the United States, Europe and India combined. The US government can prevent US companies from using Chinese models, but it can’t stop the rest of the world from using them. That won’t stop China from becoming the leader in AI. Digital intelligence comes down to how much AI compute, how many chips and how much electricity you have. The current constraint is electricity outside China. In China, the constraint is chips. China is also closer than most people realize to solving the lithography problem, which would enable it to make AI chips in very large volumes. Once we address the power constraint with AI data centers in space, the constraint will once again be chips outside China.”
4:51

Elon Musk explains how data centers in Space could help the US compete with China in AI “Given that Chinese AI companies are doing as well as they are with a relatively small amount of compute, it seems that if they had a lot of compute, there’s a good chance they would be the leaders. The constraints on AI are essentially electricity and AI chips. China is very strong in digital AI, and it has far more electricity than the United States. In fact, China already has more electricity than the United States, Europe and India combined. The US government can prevent US companies from using Chinese models, but it can’t stop the rest of the world from using them. That won’t stop China from becoming the leader in AI. Digital intelligence comes down to how much AI compute, how many chips and how much electricity you have. The current constraint is electricity outside China. In China, the constraint is chips. China is also closer than most people realize to solving the lithography problem, which would enable it to make AI chips in very large volumes. Once we address the power constraint with AI data centers in space, the constraint will once again be chips outside China.”

DogeDesigner

244,339 views • 29 days ago

🇨🇳 CHINA IS ALMOST READY TO UNDERCUT THE WORLD'S BEST AI MODELS. Six months ago, that sounded impossible. Today GLM-5.2 is open source and costs a fraction of frontier models. Zhipu's co-founder says Fable-class Chinese AI comes even sooner than people think. This is the same playbook China ran on solar, on steel, on EVs. Build it cheaper. Give it away. Take the market. If China delivers frontier AI at a fraction of the price, the economics holding up the U.S. AI market start to crack.
0:20

🇨🇳 CHINA IS ALMOST READY TO UNDERCUT THE WORLD'S BEST AI MODELS. Six months ago, that sounded impossible. Today GLM-5.2 is open source and costs a fraction of frontier models. Zhipu's co-founder says Fable-class Chinese AI comes even sooner than people think. This is the same playbook China ran on solar, on steel, on EVs. Build it cheaper. Give it away. Take the market. If China delivers frontier AI at a fraction of the price, the economics holding up the U.S. AI market start to crack.

CryptoGoos

46,766 views • 2 months ago

JD Vance on China and AI: I'm not sure many Americans have a good understanding of how the Chinese actually think about AI. I think there's a part of Xi's inner circle that probably just wants to dominate the AI arms race. I actually think there is a part of Xi's inner circle that says, "We don't want to lose to the United States, but we don't want to win either." They're, I think, a little freaked out by it, is what I'm saying. Source: The Michael Knowles Show
0:41

JD Vance on China and AI: I'm not sure many Americans have a good understanding of how the Chinese actually think about AI. I think there's a part of Xi's inner circle that probably just wants to dominate the AI arms race. I actually think there is a part of Xi's inner circle that says, "We don't want to lose to the United States, but we don't want to win either." They're, I think, a little freaked out by it, is what I'm saying. Source: The Michael Knowles Show

Clash Report

34,559 views • 1 month ago

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

281,024 views • 3 months ago

The Rise of Chinese girls in America. In 2018, Charlie Munger explained why Americans have so many adopted Chinese Girls. “Every American private school is full of the discarded Chinese girls and they're getting all A's and winning prizes” Charlie explains why this happened: “Because there was so much poverty in China and it was so overpopulated, if an American couple who had no child of their own, they could go to China and adopt a poor Chinese girl.” He makes a very important point: “So in every important city of America, people soon learned that they got better babies by taking the unwanted Chinese girls from the Chinese farms. Those babies on average worked out better than if they had their own children. So everyone wanted a Chinese girl." Charlie explained how they are winning in America: "Every American private school is full of the discarded Chinese girls and they're getting all A's and winning prizes. They're spectacularly successful. You go to Minnesota and see these Chinese girls, they're playing the difficult instruments in the orchestra."
1:29

The Rise of Chinese girls in America. In 2018, Charlie Munger explained why Americans have so many adopted Chinese Girls. “Every American private school is full of the discarded Chinese girls and they're getting all A's and winning prizes” Charlie explains why this happened: “Because there was so much poverty in China and it was so overpopulated, if an American couple who had no child of their own, they could go to China and adopt a poor Chinese girl.” He makes a very important point: “So in every important city of America, people soon learned that they got better babies by taking the unwanted Chinese girls from the Chinese farms. Those babies on average worked out better than if they had their own children. So everyone wanted a Chinese girl." Charlie explained how they are winning in America: "Every American private school is full of the discarded Chinese girls and they're getting all A's and winning prizes. They're spectacularly successful. You go to Minnesota and see these Chinese girls, they're playing the difficult instruments in the orchestra."

Ronit Pereira

642,439 views • 4 months ago

China ‘Rent-a-Womb Industry EXPOSED: Motels full of pregnant woman discovered in California “Chinese couples are hiring American surrogates and having them give birth to their kids in America. Then the Chinese couple comes over after the birth and takes the kid back to China with a U.S. passport” “it's happened tens of thousands of times across the United States” “While we were in California, we learned about this new rent-a-womb scheme, which is almost more alarming because it is not illegal. It's a loophole. This is actually one of the motels (see video) that we went into where some of the pregnant women stay. Basically with the rent-a-wombs, you've got these parents in China who spend hundreds of thousands of dollars, it's happening thousands of times They pay a woman in America, they have thr sperm and the egg from China inside of them. They use the American womb. The American woman gives birth to the Chinese baby and then the baby gets the U.S. passport but immediately goes back to China with no allegiance whatsoever to America but is an American citizen.”
3:54

China ‘Rent-a-Womb Industry EXPOSED: Motels full of pregnant woman discovered in California “Chinese couples are hiring American surrogates and having them give birth to their kids in America. Then the Chinese couple comes over after the birth and takes the kid back to China with a U.S. passport” “it's happened tens of thousands of times across the United States” “While we were in California, we learned about this new rent-a-womb scheme, which is almost more alarming because it is not illegal. It's a loophole. This is actually one of the motels (see video) that we went into where some of the pregnant women stay. Basically with the rent-a-wombs, you've got these parents in China who spend hundreds of thousands of dollars, it's happening thousands of times They pay a woman in America, they have thr sperm and the egg from China inside of them. They use the American womb. The American woman gives birth to the Chinese baby and then the baby gets the U.S. passport but immediately goes back to China with no allegiance whatsoever to America but is an American citizen.”

Wall Street Apes

3,754,527 views • 1 year ago

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

252,434 views • 1 month ago

2025.02.04 Roy from the New Federal State of China whistleblows that Liang Wenfeng, the CEO of DeepSeek, is a member of the third department of the General Staff of PLA, just like Zhang Yiming, the CEO of ByteDance, who is also from the PLA. The Chinese Communist Party has over a hundred so-called 'startups' in Hangzhou backed by the PLA. If the United States does not take action to decouple from CCP's technology, it will cause devastating damage to the U.S. stock market. For the latest intelligence and information, follow the NFSCSpeaks account on GETTR and X.
3:04

2025.02.04 Roy from the New Federal State of China whistleblows that Liang Wenfeng, the CEO of DeepSeek, is a member of the third department of the General Staff of PLA, just like Zhang Yiming, the CEO of ByteDance, who is also from the PLA. The Chinese Communist Party has over a hundred so-called 'startups' in Hangzhou backed by the PLA. If the United States does not take action to decouple from CCP's technology, it will cause devastating damage to the U.S. stock market. For the latest intelligence and information, follow the NFSCSpeaks account on GETTR and X.

NFSC Speaks

34,921 views • 1 year ago

Good news! As 🤠Weimar Paper Baron🤠 and Bai, Xiaojun have reported, most Chinese state-owned commercial banks have already resumed their #Gold accumulate programs and physical #Gold withdrawals by Chinese citizens. Here is a video taken on Nov 4, 2025 around 11:20 am Beijing Time by a Chinese citizen who withdrew physical #Gold from China Construction Bank. As you can see the #Gold is VAT EXEMPT! The withdrawal price of physical #Gold from China Construction bank today is 924 RMB Yuan/gram which is the equivalent of 4019 USD/Troy Ounce.
1:24

Good news! As 🤠Weimar Paper Baron🤠 and Bai, Xiaojun have reported, most Chinese state-owned commercial banks have already resumed their #Gold accumulate programs and physical #Gold withdrawals by Chinese citizens. Here is a video taken on Nov 4, 2025 around 11:20 am Beijing Time by a Chinese citizen who withdrew physical #Gold from China Construction Bank. As you can see the #Gold is VAT EXEMPT! The withdrawal price of physical #Gold from China Construction bank today is 924 RMB Yuan/gram which is the equivalent of 4019 USD/Troy Ounce.

Eric Yeung 👍🚀🌕

20,797 views • 9 months ago

China just released an open source AI model that matches the best closed models from OpenAI and Anthropic. Gavin Baker explained exactly how they did it and the answer should concern every American AI lab. The model is called GLM 5.2. It was built by Z. AI. You get 744 billion parameters, 1 million token context window and its MIT license, meaning anyone can download it, fork it, build a company on it, with no restrictions and no Dario. It scored 51 points on the artificial analysis intelligence index. The highest score any open weight model has ever achieved. It beat GPT 5.5 on the frontier software engineering benchmark. It trails Claude Opus 4.8 by less than one percentage point. And it costs 85% less to run than GPT 5.5 for comparable performance. Gavin Baker said on the All-In podcast that this model has challenged some of his beliefs. Then he explained how China built it. The method is called distillation. Just think of tens of thousands of phones and computers running simultaneously, all hitting the frontier model APIs through masked accounts, asking specific questions, and harvesting what happens inside the model when it answers. Every reasoning step, every token. The entire thinking process gets recorded and fed back into the Chinese model during training. It is a cheat sheet. It is the answer key to the exam. And here is the part that should worry everyone. Sacks said it plainly. China was already nine months behind American models. But now that GLM 5.2 is good enough to run its own reinforcement learning, it can improve itself without needing to distill from American models anymore. The cheat sheet let them get close enough to start writing their own answers. Sacks said we are six months behind on the model and 24 months behind on silicon and they are only a few months behind in total. The Z. AI founder told Elon Musk directly that open weight fable-level capability will be here before Q1 2027. Every restriction Anthropic lobbied for, every self-imposed safety guardrail, every month of delay in releasing American frontier models accelerated this. The Chinese labs were not under those restrictions. They were not going to wait. The composable model future Gavin described, where every enterprise runs a frontier model alongside their own fine-tuned open weight model, is coming regardless of what American labs do next. The question is just whether the open weight half of that stack is American or Chinese. Right now it is Chinese. WATCH THE FULL PODCAST ON The All-In Podcast
3:21

China just released an open source AI model that matches the best closed models from OpenAI and Anthropic. Gavin Baker explained exactly how they did it and the answer should concern every American AI lab. The model is called GLM 5.2. It was built by Z. AI. You get 744 billion parameters, 1 million token context window and its MIT license, meaning anyone can download it, fork it, build a company on it, with no restrictions and no Dario. It scored 51 points on the artificial analysis intelligence index. The highest score any open weight model has ever achieved. It beat GPT 5.5 on the frontier software engineering benchmark. It trails Claude Opus 4.8 by less than one percentage point. And it costs 85% less to run than GPT 5.5 for comparable performance. Gavin Baker said on the All-In podcast that this model has challenged some of his beliefs. Then he explained how China built it. The method is called distillation. Just think of tens of thousands of phones and computers running simultaneously, all hitting the frontier model APIs through masked accounts, asking specific questions, and harvesting what happens inside the model when it answers. Every reasoning step, every token. The entire thinking process gets recorded and fed back into the Chinese model during training. It is a cheat sheet. It is the answer key to the exam. And here is the part that should worry everyone. Sacks said it plainly. China was already nine months behind American models. But now that GLM 5.2 is good enough to run its own reinforcement learning, it can improve itself without needing to distill from American models anymore. The cheat sheet let them get close enough to start writing their own answers. Sacks said we are six months behind on the model and 24 months behind on silicon and they are only a few months behind in total. The Z. AI founder told Elon Musk directly that open weight fable-level capability will be here before Q1 2027. Every restriction Anthropic lobbied for, every self-imposed safety guardrail, every month of delay in releasing American frontier models accelerated this. The Chinese labs were not under those restrictions. They were not going to wait. The composable model future Gavin described, where every enterprise runs a frontier model alongside their own fine-tuned open weight model, is coming regardless of what American labs do next. The question is just whether the open weight half of that stack is American or Chinese. Right now it is Chinese. WATCH THE FULL PODCAST ON The All-In Podcast

Ihtesham Ali

86,295 views • 1 month ago

Business professor Scott Galloway says China is flooding the world with dirt-cheap AI models on purpose, and it’s wrecking American AI companies faster than cheap Japanese cars ever wrecked Detroit. “Free Chinese models went from less than a third of all traffic in late 2025 to about two-thirds recently.” “They steal the IP on a cell phone tower from Siemens, and then they manufacture it with cheaper labor and they sell it back for 40 cents on the dollar.” “The best business model in history is IP theft.” “What the Chinese automobile industry did to Detroit in about three decades, it feels like Beijing is doing to us in AI frontier models in about three months.”
2:37

Business professor Scott Galloway says China is flooding the world with dirt-cheap AI models on purpose, and it’s wrecking American AI companies faster than cheap Japanese cars ever wrecked Detroit. “Free Chinese models went from less than a third of all traffic in late 2025 to about two-thirds recently.” “They steal the IP on a cell phone tower from Siemens, and then they manufacture it with cheaper labor and they sell it back for 40 cents on the dollar.” “The best business model in history is IP theft.” “What the Chinese automobile industry did to Detroit in about three decades, it feels like Beijing is doing to us in AI frontier models in about three months.”

ileri 𖣂

125,429 views • 1 month ago

A Chinese netizen used AI to create a "post-capitalism America" video in which Americans learned from Chinese governance practices, with the government serving its people, resolving social issues such as homelessness, poverty, and high-cost medical care, and improving infrastructure for citizens. Chinese public now regard the United States with greater objectivity and empathy after the influx of American Xiaohongshu refugees and the trending of the "American kill line" topic on social media. Using AI, the Chinese netizens have spread their wish to the American working class, who are yearning for a decent life and a reasonable pay that is worthy of their hard work. This is a good illustration of how the internet has brought the global working class closer together via the common experiences and struggles they face. AI video made by: 厉祚Legacy
4:15

A Chinese netizen used AI to create a "post-capitalism America" video in which Americans learned from Chinese governance practices, with the government serving its people, resolving social issues such as homelessness, poverty, and high-cost medical care, and improving infrastructure for citizens. Chinese public now regard the United States with greater objectivity and empathy after the influx of American Xiaohongshu refugees and the trending of the "American kill line" topic on social media. Using AI, the Chinese netizens have spread their wish to the American working class, who are yearning for a decent life and a reasonable pay that is worthy of their hard work. This is a good illustration of how the internet has brought the global working class closer together via the common experiences and struggles they face. AI video made by: 厉祚Legacy

Eivor

104,367 views • 7 months ago

What's the Big Deal with DeepSeek in AI? Here's why DeepSeek is making everyone take notice: 1. Super Smart on a Budget: DeepSeek showed you can make awesome AI without breaking the bank. Their latest model, DeepSeek-V3, was trained for only about $10 million, which is a lot less than the usual big bucks spent on AI, like the rumored $78 million for some of OpenAI's models. They did this in just two months with fewer fancy computers. 2. Open for Everyone: DeepSeek isn't keeping their tech a secret. They've made it open-source, meaning anyone can use, tweak, and learn from it. It's like they're saying, "Come join the party!" 3. Beating the Big Names: DeepSeek-V3 has done better than some top dogs from companies like OpenAI and Google in solving puzzles, math, and coding. This proves you can get great AI results without spending a fortune. 4. Challenging NVIDIA: NVIDIA's chips are usually the choice for AI because they're really powerful. But since DeepSeek did so well with less expensive chips, it might make people think twice about always going for NVIDIA's priciest options. 5. The DeepSeek Crew: The team at DeepSeek is young and smart, mostly from top Chinese schools, with brains in physics, math, and computer science. They learned AI in about six months by themselves! They use first principle thinking, which means they break down problems to the basics and build from there. This has helped them come up with cool new ways to do AI. 6. Changing AI for Good: DeepSeek is showing that AI can be cheaper and more open to everyone. They're changing how we think AI should be made and shared, which could shake up the whole AI world. So, as we watch DeepSeek, it's clear they're not just another player; they're changing the rules of the game. I predicted that this would be a make or break year for all the massive investments made in AI by American VC's. A few weeks later, DeepSeek happens! Watch the rest of my predictions in my 2025 outlook video . Link in replies #AIInnovation #DeepSeek #NVIDIA #OpenAI #TechDisruption
0:44

What's the Big Deal with DeepSeek in AI? Here's why DeepSeek is making everyone take notice: 1. Super Smart on a Budget: DeepSeek showed you can make awesome AI without breaking the bank. Their latest model, DeepSeek-V3, was trained for only about $10 million, which is a lot less than the usual big bucks spent on AI, like the rumored $78 million for some of OpenAI's models. They did this in just two months with fewer fancy computers. 2. Open for Everyone: DeepSeek isn't keeping their tech a secret. They've made it open-source, meaning anyone can use, tweak, and learn from it. It's like they're saying, "Come join the party!" 3. Beating the Big Names: DeepSeek-V3 has done better than some top dogs from companies like OpenAI and Google in solving puzzles, math, and coding. This proves you can get great AI results without spending a fortune. 4. Challenging NVIDIA: NVIDIA's chips are usually the choice for AI because they're really powerful. But since DeepSeek did so well with less expensive chips, it might make people think twice about always going for NVIDIA's priciest options. 5. The DeepSeek Crew: The team at DeepSeek is young and smart, mostly from top Chinese schools, with brains in physics, math, and computer science. They learned AI in about six months by themselves! They use first principle thinking, which means they break down problems to the basics and build from there. This has helped them come up with cool new ways to do AI. 6. Changing AI for Good: DeepSeek is showing that AI can be cheaper and more open to everyone. They're changing how we think AI should be made and shared, which could shake up the whole AI world. So, as we watch DeepSeek, it's clear they're not just another player; they're changing the rules of the game. I predicted that this would be a make or break year for all the massive investments made in AI by American VC's. A few weeks later, DeepSeek happens! Watch the rest of my predictions in my 2025 outlook video . Link in replies #AIInnovation #DeepSeek #NVIDIA #OpenAI #TechDisruption

Dr Ola Brown

83,460 views • 1 year ago

Cloud capital versus AI - What DeepSeek’s spectacular success means for technofeudalism & the New Cold War DeepSeek, a Chinese artificial intelligence (AI) company, this week changed the global AI landscape, not to mention caused $1 trillion losses in the New York stock exchange and the NASDAC. In the process, it demonstrated the difference between cloud capital, which drives technofeudalism onward and upward, and AI-services, which were always a bubble waiting to burst. What remains to be seen is DeepSeek's impact on the New Cold War between the US and China which, from its beginning, was motivated by the clash between US and Chinese cloud capital. DeepSeek is China's response to OpenAI's ChatGPT. Its models perform as efficiently as their US counterparts. The difference is that DeepSeek is offered for free, making money only by selling services to developers - not to the public – at a fraction of the price OpenAI charges! The gist of DeepSeek’s arrival on the AI scene is a sudden transition from proprietary to open source technology. It is, therefore, no great wonder that, the moment DeekSeek became the most downloaded app on the Apple Store, it pulverised the market capitalisation of the, hitherto overinflated, US Big Tech companies. But how did this happen? How is a private commodity suddenly being offered for free? And does this mean that technofeudalism is in trouble? To begin with it is important to note AI was never a proprietary technology in itself. The underlying code has always been open source. What made AI quasi-private was the way these models were trained using huge amounts of privatised (that is stolen from us) data. A leaked Google memo in 2017, that was widely discussed in the industry at the time, but also widely refuted, explained: "If an open source LLM trained for a few million dollars outperforms the effectiveness of proprietary models... There will be no firewall to safeguard OpenAI either." DeepSeek pierced the US AI companies’ bubble by decommodifying the results of the model’s training, shifting them from behind a paywall to the public arena. Within days, developers around the world started building their own models on top of DeepSeek's. This is was the nightmare for US Big Tech's AI service providers who offered the results of prompts as a commodity, in the form of subscriptions. DeepSeek-type applications can now produce high-quality translations for free and, in so doing, undermine companies specialising in, for example, translation services, such as Germany's Deepl. In the broader scheme of things, this means that the morsels of cloud capital that Europe owns has lost its market value. Nevertheless, and this is a huge nevertheless, it is only AI-as-a-commodity that has lost its (grossly exaggerated) value. In sharp contrast, cloud capital utilised not as a commodity producing piece of tech but as produced means of behavioural modification is not at all threatened by companies like DeepSeek. And since technofeudalism is powered by cloud capital working that way, rather than commodity-like AI services of the ChaptGPT type, our technofeudal order is not threatened by competitors such as DeepSeek. To help understand the difference between cloud capital and AI-based commodified services it helps to compare and contrast Alexa and ChatGPT. Alexa is not offering you a commodified service. It is your free pretend-slave. Unlike ChatGPT you do not pay a subscription to Amazon for the right to order Alexa to order you milk or to switch off your lights. Instead, you train Alexa to train you to train it to know you so that it wins your trust with good recommendations so that it can modify your behaviour – ‘encourage’ you to buy a commodity from with Bezos retaining up to 40% of the price you pay (as a cloud rent). In short, the work that Alexa performs for you is not a commodity, unlike ChatGPT which works to sell you a commodity. In other words, ChatGPT is subject to market competition, to the likes of DeepSeek, but Alexa is not. This is why OpenAI, ChatGPT’s maker, is seriously damaged by the emergence of DeepSeek but Amazon is not. Thus, my basic point: Cloud capital is in a league of its own, beyond market competition from DeepSeek-like upstarts, because its power lies in its capacity to modify our behaviour and remove us from any market (e.g., to shift us from real markets to cloud fiefs like Amazon and Alibaba). In conclusion, cloud capital’s capacity to drive technofeudalism is not challenged by companies like DeepSeek. Only companies like OpenAI, which invested so much and so foolishly in providing a commodified service, stand to lose enormously. Yet another sign that capitalism is dead at the hand of cloud capital while technofeudalism is going from strength to strength and, as it does so, fuels even further the New Cold War between the US and China which in my book, Technofeudalism, I have explained away as the clash of the two huge concentrations of cloud capital: the American dollar-denominated super cloudalist power and the Chinese yuan-denominated one. Speaking of this New Cold War, which I have argued is mostly fuelled by the clash between American and Chinese cloud capital, I wonder what impact DeepSeek’s success will have on the US government. Silicon Valley and Washington DC had convinced themselves that America had a huge AI lead over China. Now, a tiny Chinese company has destroyed that confidence by producing on a shoestring better AI tech than Sillicon Valley had imagined possible. I can almost hear the whirring inside the heads of people in power on both America’s East and West Coast thinking that if the Chinese can do this out of the blue, what else can they do tomorrow? It is reminiscent of the Sputnik moment, isn’t it? It will be interesting to see how Trump reacts to this threat to companies American AI companies, especially since Elon Musk understands, and has spoken out against, the folly of commodifying AI services rather than going full on technofeudal. These are interesting times, in the traditional Chinese sense of the phrase.
9:27

Cloud capital versus AI - What DeepSeek’s spectacular success means for technofeudalism & the New Cold War DeepSeek, a Chinese artificial intelligence (AI) company, this week changed the global AI landscape, not to mention caused $1 trillion losses in the New York stock exchange and the NASDAC. In the process, it demonstrated the difference between cloud capital, which drives technofeudalism onward and upward, and AI-services, which were always a bubble waiting to burst. What remains to be seen is DeepSeek's impact on the New Cold War between the US and China which, from its beginning, was motivated by the clash between US and Chinese cloud capital. DeepSeek is China's response to OpenAI's ChatGPT. Its models perform as efficiently as their US counterparts. The difference is that DeepSeek is offered for free, making money only by selling services to developers - not to the public – at a fraction of the price OpenAI charges! The gist of DeepSeek’s arrival on the AI scene is a sudden transition from proprietary to open source technology. It is, therefore, no great wonder that, the moment DeekSeek became the most downloaded app on the Apple Store, it pulverised the market capitalisation of the, hitherto overinflated, US Big Tech companies. But how did this happen? How is a private commodity suddenly being offered for free? And does this mean that technofeudalism is in trouble? To begin with it is important to note AI was never a proprietary technology in itself. The underlying code has always been open source. What made AI quasi-private was the way these models were trained using huge amounts of privatised (that is stolen from us) data. A leaked Google memo in 2017, that was widely discussed in the industry at the time, but also widely refuted, explained: "If an open source LLM trained for a few million dollars outperforms the effectiveness of proprietary models... There will be no firewall to safeguard OpenAI either." DeepSeek pierced the US AI companies’ bubble by decommodifying the results of the model’s training, shifting them from behind a paywall to the public arena. Within days, developers around the world started building their own models on top of DeepSeek's. This is was the nightmare for US Big Tech's AI service providers who offered the results of prompts as a commodity, in the form of subscriptions. DeepSeek-type applications can now produce high-quality translations for free and, in so doing, undermine companies specialising in, for example, translation services, such as Germany's Deepl. In the broader scheme of things, this means that the morsels of cloud capital that Europe owns has lost its market value. Nevertheless, and this is a huge nevertheless, it is only AI-as-a-commodity that has lost its (grossly exaggerated) value. In sharp contrast, cloud capital utilised not as a commodity producing piece of tech but as produced means of behavioural modification is not at all threatened by companies like DeepSeek. And since technofeudalism is powered by cloud capital working that way, rather than commodity-like AI services of the ChaptGPT type, our technofeudal order is not threatened by competitors such as DeepSeek. To help understand the difference between cloud capital and AI-based commodified services it helps to compare and contrast Alexa and ChatGPT. Alexa is not offering you a commodified service. It is your free pretend-slave. Unlike ChatGPT you do not pay a subscription to Amazon for the right to order Alexa to order you milk or to switch off your lights. Instead, you train Alexa to train you to train it to know you so that it wins your trust with good recommendations so that it can modify your behaviour – ‘encourage’ you to buy a commodity from with Bezos retaining up to 40% of the price you pay (as a cloud rent). In short, the work that Alexa performs for you is not a commodity, unlike ChatGPT which works to sell you a commodity. In other words, ChatGPT is subject to market competition, to the likes of DeepSeek, but Alexa is not. This is why OpenAI, ChatGPT’s maker, is seriously damaged by the emergence of DeepSeek but Amazon is not. Thus, my basic point: Cloud capital is in a league of its own, beyond market competition from DeepSeek-like upstarts, because its power lies in its capacity to modify our behaviour and remove us from any market (e.g., to shift us from real markets to cloud fiefs like Amazon and Alibaba). In conclusion, cloud capital’s capacity to drive technofeudalism is not challenged by companies like DeepSeek. Only companies like OpenAI, which invested so much and so foolishly in providing a commodified service, stand to lose enormously. Yet another sign that capitalism is dead at the hand of cloud capital while technofeudalism is going from strength to strength and, as it does so, fuels even further the New Cold War between the US and China which in my book, Technofeudalism, I have explained away as the clash of the two huge concentrations of cloud capital: the American dollar-denominated super cloudalist power and the Chinese yuan-denominated one. Speaking of this New Cold War, which I have argued is mostly fuelled by the clash between American and Chinese cloud capital, I wonder what impact DeepSeek’s success will have on the US government. Silicon Valley and Washington DC had convinced themselves that America had a huge AI lead over China. Now, a tiny Chinese company has destroyed that confidence by producing on a shoestring better AI tech than Sillicon Valley had imagined possible. I can almost hear the whirring inside the heads of people in power on both America’s East and West Coast thinking that if the Chinese can do this out of the blue, what else can they do tomorrow? It is reminiscent of the Sputnik moment, isn’t it? It will be interesting to see how Trump reacts to this threat to companies American AI companies, especially since Elon Musk understands, and has spoken out against, the folly of commodifying AI services rather than going full on technofeudal. These are interesting times, in the traditional Chinese sense of the phrase.

Yanis Varoufakis

96,322 views • 1 year ago

Gavin Baker Gavin Baker says open source is "awesome" for AI infrastructure names because it shifts the economic value from the frontier labs to the infrastructure, and it is already 80% plus of all tokens processed. "A misconception that a lot of people have is that open source models are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.
0:37

Gavin Baker Gavin Baker says open source is "awesome" for AI infrastructure names because it shifts the economic value from the frontier labs to the infrastructure, and it is already 80% plus of all tokens processed. "A misconception that a lot of people have is that open source models are somehow bad for AI. They're awesome for the AI infrastructure providers. They just shift economic value from the margins of the frontier labs to the infrastructure." "But I do think there's still a role for these frontier models. And it may be true, to date, frontier tokens are capturing 90% of the economic value, and open source tokens are probably 80% plus of tokens processed, and those ratios may be here to stay." _______ Follow Fireside Alpha for more highlights of the best business and technology conversations.

Fireside Alpha

162,832 views • 1 month ago