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Scott Galloway just explained why China doesn’t need to build better AI than America. It only needs to make American AI worthless. Galloway: “I think China is beginning to engage in what I’ll call AI dumping.” Not competing. Dumping. It’s the term economists use for flooding a foreign market... with below-cost goods until the domestic industry collapses. Galloway: “They’re going to have a series of open-weight models. About a third of corporations now are supposedly using Chinese lightweight open-weight models that are cheaper.” Not better. Cheaper. A third of corporations. Already. China isn’t trying to out-innovate Silicon Valley. It’s trying to collapse the economics beneath it. Price warfare at the infrastructure layer. Galloway: “If I were Xi, I would just dump cheap AI into the US market.” This playbook is old. China ran it with steel. Ran it with solar. Ran it with semiconductors. Flood a market with a cheaper version until the domestic industry can’t sustain itself. AI is next. Galloway: “The moment large corporations start announcing they’re disengaging these multi-million dollar site licenses with Anthropic or OpenAI, they’re using these inexpensive Chinese models…” One CFO after another decides the Chinese model at a fraction of the cost is good enough. Not better. Good enough. “Good enough” at a lower price has killed more market leaders than any superior product ever has. Galloway: “…and the market realizes that there’s no way they can justify these incredible valuations, I think the US market crashes.” Not because the technology failed. Because the business model did. American AI companies are valued on the assumption that corporations will pay premium prices for premium models. China’s whole strategy is to make that assumption false. Galloway: “40% of the S&P now is directly or tangentially related to this giant bet America’s making on AI.” 40% of the S&P. Tied to one sector. Galloway: “The majority of GDP growth over the last two years has come from AI CapEx.” The majority of GDP growth. From one source. America didn’t diversify its future. It concentrated everything into a single bet, then left that bet undefended. Galloway: “If that slows down, we are immediately in a recession.” Immediately. Not gradually. Not over quarters. The distance between AI boom and American recession is one procurement decision. America built the most advanced AI on Earth and forgot to build an economy that survives someone selling it cheaper. The threat to American AI was never that China would build something smarter. It was that China would build something cheaper, and American corporations would choose the price. China’s real weapon isn’t Chinese technology. It’s American capitalism. The same rational self-interest that built the AI industry will dismantle it the moment a cheaper alternative appears. The market has no patriotism. Only price sensitivity. The technology race was never the real race. The real race was always whether America could turn its AI dominance into something that survives being undercut. America hasn’t even started running it. China already has.show more

Dustin

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Jensen Huang just made the most direct argument of his career about why banning Nvidia from China is not a national security strategy but rather a national security failure. Dwarkesh asks why Nvidia should be allowed to sell chips to China at all, if China would just use Huawei chips without them. Jensen's answer was that in the absence of a better choice, you take the only choice you have. As long as China has to settle for inferior chips, they are building their AI infrastructure on a foundation that is slower, harder to program, and years behind American technology. The moment the US decides to ban Nvidia from selling to China entirely, it removes that disadvantage. China is 40 percent of the global technology industry, Jensen said. Conceding that market, handing it entirely to Huawei is a disservice to American national security, American technology leadership, and American economic power. The data shows what has already happened since the export bans tightened. Nvidia's share of China's AI chip market collapsed from 95 percent to 55 percent in 2025 and at one point during the H20 ban, Jensen himself declared Nvidia had gone from 95 percent share to zero on advanced accelerators. The Trump administration's ban on H20 chips cost Nvidia an estimated 15 billion dollars in lost sales, plus a 4.5 billion dollar inventory write-down. Without the export controls, Nvidia was on track to generate roughly 23 billion dollars in H20 chip sales to China in 2025 alone. Meanwhile Huawei shipped 812,000 AI chips in 2025 and Beijing has now mandated that all state-funded data centers must switch to domestic chips. Jensen's deeper argument is about the global stack, not the quarterly revenue. When developers around the world build AI on CUDA, Nvidia's programming platform, they are building on American technology. When those AI models deploy into every country, the American stack goes with them. Cutting Nvidia out of China does not slow Chinese AI but rather accelerates the construction of a parallel Chinese tech stack that, once built at scale, competes with American technology everywhere else in the world.

Milk Road AI

21,133 просмотров • 3 месяцев назад

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.”

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

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Saying it “doesn’t matter” whether America or China wins the AI race is dangerously naïve. This is like arguing that it would not have mattered if the Soviets beat the US to a nuclear weapon. American nuclear superiority kept the Cold War cold. If we want to do the same with China today, we must win this race as well. It mattered when the Soviet Union built nuclear weapons—and it matters now as the Chinese Communist Party seeks dominance in AI and advanced chips. America must lead in the technologies that shape freedom and security.

Saying it “doesn’t matter” whether America or China wins the AI race is dangerously naïve. This is like arguing that it would not have mattered if the Soviets beat the US to a nuclear weapon. American nuclear superiority kept the Cold War cold. If we want to do the same with China today, we must win this race as well. It mattered when the Soviet Union built nuclear weapons—and it matters now as the Chinese Communist Party seeks dominance in AI and advanced chips. America must lead in the technologies that shape freedom and security.

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CryptoGoos

39,046 просмотров • 1 месяц назад

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Jensen Huang just delivered the most important warning no one in Washington is ready to hear. Not about China. About what America is doing to itself. Huang: “We should always have the best technology here. We should always have the most technology here, and the first. But we should also try to compete and win around the world.” Washington heard that and locked onto China. Jensen wasn’t talking about China. He was talking about India. The Middle East. Africa. Southeast Asia. The next two billion people coming online. All of them about to build on somebody’s AI stack. The question was never whether they get the technology. The question is whose name is on it. Huang: “It requires some amount of nuance, some amount of maturity, instead of absolutes. The world is just not absolute.” Washington doesn’t do nuance. Washington does ban lists. Restriction is now the entire American AI strategy. Not deployment. Not adoption. Not global capture. Restriction. As if you win a technology race by refusing to run it. And nobody in Washington understands what happens when you cut somebody off. They don’t stop. They build their own. Every restriction is an invitation to innovate without you. Every ban is a blueprint for independence. Every chip you refuse to sell is a chip someone else learns how to make. You are not slowing competitors down. You are giving them the one thing they never had before. Motivation to never need you again. That is not a hypothetical. That is the pattern. Every single time. Countries that cannot count on American access stop waiting for it. They invest. They recruit. They accelerate. They make breakthroughs they never would have made if Washington had just shown up and competed. You don’t contain progress by withholding it. You pour jet fuel on the one outcome you were trying to prevent. Meanwhile the people making these decisions have never built anything. Not a chip. Not a model. Not a product. Not a company. Bureaucrats writing regulation for an industry they cannot even describe accurately. Committees moving at the speed of subcommittee. And the entire American AI future is being filtered through people whose greatest technological achievement is a shared Google Doc. And here is what no one in that room wants to admit. The United States is not competing against Chinese technology. It is competing against Chinese willingness to show up. While Congress debates which chips to block, Beijing is already on a plane. Signing infrastructure deals across four continents. Not with better hardware. With available hardware. And available has beaten superior in every technology war ever fought. VHS over Betamax. Android over iOS globally. The best product never wins. The most adopted one does. Standards are not products. Standards are dependency. The kind that compounds for generations. Every country running American AI is locked into the American ecosystem permanently. Every country that isn’t belongs to somebody else. And every country America cut off is now building infrastructure designed to ensure it never has to ask again. Huang: “Your policy and what you imagined literally caused the United States to concede the second largest market in the world for no good reason at all.” That is not an opinion. That is the man building the infrastructure of the future telling Washington it is engineering its own irrelevance. The cruelest part is not that America could lose the AI race. It is that America could lose it while being absolutely certain it is winning. Because restriction feels like power. It feels like control. Like dominance. Like you are holding every card. But you are not holding anything. You are just not playing. And every day you sit there writing rules instead of shipping technology, someone else is filling the vacuum you created. History never remembers who built the best technology. Only whose technology the world was already running on when it mattered.

Dustin

46,030 просмотров • 2 месяцев назад

.Marc Andreessen 🇺🇸 says the winner of the US-China AI race could dictate what all 8 billion people on Earth use — but open source introduces a third possibility: "The stakes are basically: what is the world going to run on?" "In the long run, somebody's gonna win. And the world will either be running on American AI or be running on Chinese AI." "The open source thing is super fascinating because it throws a wrench into all of this. It raises a third possibility that neither the US nor China are going to be the platform — it may just be open source." Marc Andreessen with Jeetu Patel at Cisco AI Summit

.Marc Andreessen 🇺🇸 says the winner of the US-China AI race could dictate what all 8 billion people on Earth use — but open source introduces a third possibility: "The stakes are basically: what is the world going to run on?" "In the long run, somebody's gonna win. And the world will either be running on American AI or be running on Chinese AI." "The open source thing is super fascinating because it throws a wrench into all of this. It raises a third possibility that neither the US nor China are going to be the platform — it may just be open source." Marc Andreessen with Jeetu Patel at Cisco AI Summit

a16z

101,985 просмотров • 5 месяцев назад

$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 $650 billion on AI infrastructure this year. DeepSeek just showed the world you can match their output for pennies. The export controls were supposed to be America's ace card. Instead they taught China how to win without American chips, at American prices nobody can compete with. Jensen Huang was right. This is a horrible outcome. But it's the outcome America built for itself.$

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

Ricardo

280,185 просмотров • 3 месяцев назад

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.

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

251,491 просмотров • 26 дней назад

Scott Galloway is absolutely correct here and I believe this IS a strategy that China will adopt. We are already seeing companies like Open AI running out of money and ‘offering’ a stake holding to the government to raise yet more capital to keep them afloat. The American taxpayer is going to be on the hook when the shit hits the fan, make no mistake about it. Thanks to Diary of a CEO for the clip 🎥 TikTok -

Scott Galloway is absolutely correct here and I believe this IS a strategy that China will adopt. We are already seeing companies like Open AI running out of money and ‘offering’ a stake holding to the government to raise yet more capital to keep them afloat. The American taxpayer is going to be on the hook when the shit hits the fan, make no mistake about it. Thanks to Diary of a CEO for the clip 🎥 TikTok -

𝔗𝔯𝔲𝔱𝔥 𝔐𝔞𝔱𝔱𝔢𝔯𝔰

78,283 просмотров • 20 дней назад

Eric Schmidt just identified how America loses the AI war despite building better technology, and most people haven’t noticed it’s already happening. Schmidt: “The U.S. is chasing AGI.” America is fixated on one prize. Artificial General Intelligence. The god model. The moonshot that changes everything. Pouring resources into the ultimate breakthrough. China isn’t playing that game at all. Schmidt: “China is shipping day-to-day AI apps, and robotics.” Not waiting for superintelligence. Deploying current AI everywhere right now. Factory floors. Consumer devices. Supply chains. Physical robots at industrial scale. Today, not eventually. America might win the race to AGI and still lose the world. Schmidt: “If Chinese open-source models get good enough…” The strategic blindness is structural. US models are closed, proprietary, expensive. Chinese models like DeepSeek are open and free. Where does the developing world build its digital future? On technology it can access and afford. Which means Chinese. Schmidt: “Much of the world could end up building on them.” America competes for smartest AI. China competes for most embedded AI. And embedded wins. Technical superiority is worthless when the global standard already runs on your competitor’s freely available stack. Schmidt: “We better also be competing with the Chinese in day-to-day stuff.” The US places all chips on the ten-year AGI bet while handing China the entire commercial present. China deploys relentlessly. Robots, apps, infrastructure, all shipping now while America perfects research. Optimize exclusively for breakthrough and you surrender the industrial base. That base determines who controls what actually matters. Superintelligence is strategically meaningless if China owns the hardware running it, the software layer beneath it, and the deployed systems the world depends on. You can build the most advanced AI in existence. If nobody uses it because they’re locked into competitor ecosystems established years earlier while you focused on moonshots, you didn’t win. You built expensive irrelevance. This isn’t about capability. It’s deployment speed, adoption capture, and which technology becomes the foundation everything else builds on. America chases the ceiling. China is becoming the floor. And in technology, the floor matters more. Standards don’t win by being superior. They win by being everywhere first. And once established, switching costs make replacement nearly impossible regardless of technical advantages. We might invent AGI. China might own every system it runs on, every device it connects to, every market it operates in. At that point, creating the most intelligent AI while controlling none of the infrastructure it needs to function isn’t triumph. It’s building the world’s most advanced engine with no vehicle to put it in while your competitor already sold cars to everyone. The war isn’t won in labs. It’s won in factories, phones, and supply chains. And while we perfect the breakthrough, they’re winning the adoption race that actually determines who shapes the future.

Eric Schmidt just identified how America loses the AI war despite building better technology, and most people haven’t noticed it’s already happening. Schmidt: “The U.S. is chasing AGI.” America is fixated on one prize. Artificial General Intelligence. The god model. The moonshot that changes everything. Pouring resources into the ultimate breakthrough. China isn’t playing that game at all. Schmidt: “China is shipping day-to-day AI apps, and robotics.” Not waiting for superintelligence. Deploying current AI everywhere right now. Factory floors. Consumer devices. Supply chains. Physical robots at industrial scale. Today, not eventually. America might win the race to AGI and still lose the world. Schmidt: “If Chinese open-source models get good enough…” The strategic blindness is structural. US models are closed, proprietary, expensive. Chinese models like DeepSeek are open and free. Where does the developing world build its digital future? On technology it can access and afford. Which means Chinese. Schmidt: “Much of the world could end up building on them.” America competes for smartest AI. China competes for most embedded AI. And embedded wins. Technical superiority is worthless when the global standard already runs on your competitor’s freely available stack. Schmidt: “We better also be competing with the Chinese in day-to-day stuff.” The US places all chips on the ten-year AGI bet while handing China the entire commercial present. China deploys relentlessly. Robots, apps, infrastructure, all shipping now while America perfects research. Optimize exclusively for breakthrough and you surrender the industrial base. That base determines who controls what actually matters. Superintelligence is strategically meaningless if China owns the hardware running it, the software layer beneath it, and the deployed systems the world depends on. You can build the most advanced AI in existence. If nobody uses it because they’re locked into competitor ecosystems established years earlier while you focused on moonshots, you didn’t win. You built expensive irrelevance. This isn’t about capability. It’s deployment speed, adoption capture, and which technology becomes the foundation everything else builds on. America chases the ceiling. China is becoming the floor. And in technology, the floor matters more. Standards don’t win by being superior. They win by being everywhere first. And once established, switching costs make replacement nearly impossible regardless of technical advantages. We might invent AGI. China might own every system it runs on, every device it connects to, every market it operates in. At that point, creating the most intelligent AI while controlling none of the infrastructure it needs to function isn’t triumph. It’s building the world’s most advanced engine with no vehicle to put it in while your competitor already sold cars to everyone. The war isn’t won in labs. It’s won in factories, phones, and supply chains. And while we perfect the breakthrough, they’re winning the adoption race that actually determines who shapes the future.

Dustin

78,667 просмотров • 5 месяцев назад

Nvidia $NVDA CEO Jensen Huang was asked about a recent story that said he warned that China will beat the US in the AI race “That’s not what I said. What I said was China has very good AI technology. They have many AI researchers, in fact 50% of the world’s AI researchers are in China. And they develop very good AI technology. In fact, the most popular AI models in the world today, open-source models, are from China. So, they are moving very, very fast. The United States has to continue to move incredibly fast. And otherwise, otherwise – the world is very competitive, so we have to run fast.” (H/T Dan Nystedt)

Nvidia $NVDA CEO Jensen Huang was asked about a recent story that said he warned that China will beat the US in the AI race “That’s not what I said. What I said was China has very good AI technology. They have many AI researchers, in fact 50% of the world’s AI researchers are in China. And they develop very good AI technology. In fact, the most popular AI models in the world today, open-source models, are from China. So, they are moving very, very fast. The United States has to continue to move incredibly fast. And otherwise, otherwise – the world is very competitive, so we have to run fast.” (H/T Dan Nystedt)

Evan

1,946,831 просмотров • 8 месяцев назад

Chamath: "Nvidia is not doing what's in the best interest of the United States." 🇺🇸🇨🇳 "I think we can all do the math. About 47% of all of NVIDIA's revenue goes to China and Chinese-related countries." "And I think when you peel back this onion, what you will find is a whole raft of companies that were stood up to buy these Nvidia GPUs to essentially act as a waystation for China." "And I think that is the big problem." "Let's have a thought starter: if 47% of all of the AI capability and horsepower is being shipped to three Asian countries, where do you think the apps that require that amount of horsepower live?" "Is there a Cursor of Bhutan that we did not know? Is there a great shopping app in Cambodia that's come out of nowhere, that's AI powered?" "I think the answer is no." "Every single time we have an advance in the United States, how is it that Alibaba shows up with something incredible? DeepSeek shows up with something better?" "At every turn and at every step of AI, they are at the same rate or one step ahead." "To be honest with you, I think the real problem that we have is that Nvidia is not doing what is in the best interest of the United States." "You have a American company that has been working around the guidelines at every turn to try to land silicon into the hands of China." "Late last year, they introduced this thing called the H20 that was explicitly designed for China and to be compliant with US rules at the time." "Which again, gives these guys substantial performance." "This is a case where (Nvidia) has plausible deniability. I sell something to a Singaporean registered company? Plausible deniability." "What am I supposed to do? You can't expect me to audit it. I think that's what NVIDIA's answer will be to this question." "But what is the real expectation? At a minimum, the United States should have a mechanism to understand it." "It is implausible that if you did one or two layers of work, you would not find that most of this traffic is being used by Chinese organizations."

Chamath: "Nvidia is not doing what's in the best interest of the United States." 🇺🇸🇨🇳 "I think we can all do the math. About 47% of all of NVIDIA's revenue goes to China and Chinese-related countries." "And I think when you peel back this onion, what you will find is a whole raft of companies that were stood up to buy these Nvidia GPUs to essentially act as a waystation for China." "And I think that is the big problem." "Let's have a thought starter: if 47% of all of the AI capability and horsepower is being shipped to three Asian countries, where do you think the apps that require that amount of horsepower live?" "Is there a Cursor of Bhutan that we did not know? Is there a great shopping app in Cambodia that's come out of nowhere, that's AI powered?" "I think the answer is no." "Every single time we have an advance in the United States, how is it that Alibaba shows up with something incredible? DeepSeek shows up with something better?" "At every turn and at every step of AI, they are at the same rate or one step ahead." "To be honest with you, I think the real problem that we have is that Nvidia is not doing what is in the best interest of the United States." "You have a American company that has been working around the guidelines at every turn to try to land silicon into the hands of China." "Late last year, they introduced this thing called the H20 that was explicitly designed for China and to be compliant with US rules at the time." "Which again, gives these guys substantial performance." "This is a case where (Nvidia) has plausible deniability. I sell something to a Singaporean registered company? Plausible deniability." "What am I supposed to do? You can't expect me to audit it. I think that's what NVIDIA's answer will be to this question." "But what is the real expectation? At a minimum, the United States should have a mechanism to understand it." "It is implausible that if you did one or two layers of work, you would not find that most of this traffic is being used by Chinese organizations."

The All-In Podcast

910,450 просмотров • 1 год назад

Jensen Huang just told you America is in an AI arms race where half the talent building the weapons was born on the other side. Huang: “50% of the world’s AI researchers are from China. Taking it emotionally too far from that results in consequences in relationships that are just harder to manage.” That is not diplomacy. That is the CEO of the most critical company in the AI supply chain telling you the West has a structural dependency it cannot legislate away. Half the minds capable of engineering superintelligence were born, raised, and educated inside the borders of America’s primary geopolitical rival. And Washington is writing policy as if that number does not exist. The politician sees China and reaches for tariffs. Export bans. Visa restrictions. The instinct is confrontation. The endgame is severance. Huang is telling you severance is suicide. You cannot win an intelligence race by amputating half the intelligence. America does not lead AI because of its government. It leads because the best researchers on Earth chose to be here. The compute. The capital. The culture of building. That pull is not permanent. The moment it reverses, the talent does not disappear. It goes home. And it takes the knowledge with it. Every emotionally driven export ban. Every reactionary visa restriction. Every congressional hearing staged for cameras instead of outcomes. Each one is a small push in the wrong direction on a scale that does not forgive miscalculation. China is not debating whether the technology moves too fast. They are building gigawatt-scale data centers and training sovereign models with the full weight of a state that treats AI supremacy as civilizational survival. And they are doing it with a researcher pipeline that America helped build and is now actively dismantling. Huang: “We can have a healthy competition while we compete, compete fairly, and collaborate at the same time.” That sounds reasonable until you hear what he is actually saying. The only path to American AI dominance runs directly through a relationship with the country trying to beat it. That does not fit on a campaign poster. But it is the math. The AI race is not a tariff negotiation. It is the final competition for who writes the operating system every future economy, military, and government runs on. Whoever builds superintelligence first does not get a market advantage. They get a permanent one. The kind no treaty undoes. And America is treating this like a midterm election issue while China is treating it like the last war it will ever need to fight. The danger is not that China outspends the U.S. The danger is that America mistakes emotional foreign policy for strategic foreign policy and severs the very relationships keeping it ahead. The researchers are the resource. Not the chips. Not the data centers. The people who know how to make the models think. Half of them are Chinese. And the U.S. is running a geopolitical strategy that forces those people to choose. Huang sees the board. He sells the GPUs. He knows who is buying them and who is designing on them. And he is telling you the current trajectory ends with America holding the best hardware on Earth and no one left who knows how to use it. The country that wins this will not be the one with the strongest rhetoric. It will be the one that understood the difference between controlling talent and attracting it. Right now, China is attracting. America is restricting. The algorithm does not care about flags. It scales for whoever shows up with the math. And right now, half the people who know the math are being told they are not welcome.

Jensen Huang just told you America is in an AI arms race where half the talent building the weapons was born on the other side. Huang: “50% of the world’s AI researchers are from China. Taking it emotionally too far from that results in consequences in relationships that are just harder to manage.” That is not diplomacy. That is the CEO of the most critical company in the AI supply chain telling you the West has a structural dependency it cannot legislate away. Half the minds capable of engineering superintelligence were born, raised, and educated inside the borders of America’s primary geopolitical rival. And Washington is writing policy as if that number does not exist. The politician sees China and reaches for tariffs. Export bans. Visa restrictions. The instinct is confrontation. The endgame is severance. Huang is telling you severance is suicide. You cannot win an intelligence race by amputating half the intelligence. America does not lead AI because of its government. It leads because the best researchers on Earth chose to be here. The compute. The capital. The culture of building. That pull is not permanent. The moment it reverses, the talent does not disappear. It goes home. And it takes the knowledge with it. Every emotionally driven export ban. Every reactionary visa restriction. Every congressional hearing staged for cameras instead of outcomes. Each one is a small push in the wrong direction on a scale that does not forgive miscalculation. China is not debating whether the technology moves too fast. They are building gigawatt-scale data centers and training sovereign models with the full weight of a state that treats AI supremacy as civilizational survival. And they are doing it with a researcher pipeline that America helped build and is now actively dismantling. Huang: “We can have a healthy competition while we compete, compete fairly, and collaborate at the same time.” That sounds reasonable until you hear what he is actually saying. The only path to American AI dominance runs directly through a relationship with the country trying to beat it. That does not fit on a campaign poster. But it is the math. The AI race is not a tariff negotiation. It is the final competition for who writes the operating system every future economy, military, and government runs on. Whoever builds superintelligence first does not get a market advantage. They get a permanent one. The kind no treaty undoes. And America is treating this like a midterm election issue while China is treating it like the last war it will ever need to fight. The danger is not that China outspends the U.S. The danger is that America mistakes emotional foreign policy for strategic foreign policy and severs the very relationships keeping it ahead. The researchers are the resource. Not the chips. Not the data centers. The people who know how to make the models think. Half of them are Chinese. And the U.S. is running a geopolitical strategy that forces those people to choose. Huang sees the board. He sells the GPUs. He knows who is buying them and who is designing on them. And he is telling you the current trajectory ends with America holding the best hardware on Earth and no one left who knows how to use it. The country that wins this will not be the one with the strongest rhetoric. It will be the one that understood the difference between controlling talent and attracting it. Right now, China is attracting. America is restricting. The algorithm does not care about flags. It scales for whoever shows up with the math. And right now, half the people who know the math are being told they are not welcome.

Dustin

10,925 просмотров • 3 месяцев назад