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🇨🇳 🇺🇸 CHINA'S AI STACK IS GETTING DANGEROUSLY COMPETITIVE. Huawei's Ascend chips are now powering DeepSeek at a fraction of Western inference costs. The result: DeepSeek just made its 75% API price cut permanent on DeepSeek-V4-Pro. This is not a promotion. This is the new floor. The full vertical...

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CryptoGoos

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43,154 просмотров • 2 месяцев назад •via X (Twitter)

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

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

Ricardo

280,185 просмотров • 3 месяцев назад

watched through the entire interview these guys aren't in the same league. jensen plays to win. dwarkesh has been one shotted by mythos marketing. in a way its jensen arguing against dario by proxy. think there's a fundamental underestimation that most ppl in the west have about huawei. they are a freak monster powerhouse and jensen is 100% correct in wanting to push nvidia in china versus letting huawei eat the domestic market. the worst outcome for the US would be for deepseek to be trained 100% on huawei chips versus a china that is dependent on the nvidia stack.
3:58

watched through the entire interview these guys aren't in the same league. jensen plays to win. dwarkesh has been one shotted by mythos marketing. in a way its jensen arguing against dario by proxy. think there's a fundamental underestimation that most ppl in the west have about huawei. they are a freak monster powerhouse and jensen is 100% correct in wanting to push nvidia in china versus letting huawei eat the domestic market. the worst outcome for the US would be for deepseek to be trained 100% on huawei chips versus a china that is dependent on the nvidia stack.

factorydoge

543,134 просмотров • 3 месяцев назад

GenZ Pop Quiz🔬 | DeepSeek Leads the AI Wave: Career Challenges or Blue Ocean of Opportunities? Chinese tech companies like DeepSeek are making a massive splash on the world stage, totally redefining China's place in the global tech scene. Chinese AI isn't just a wave—it's a tidal wave! But what does this mean for us? Are we facing a career challenge or diving into a sea of opportunities? Let's find out what China's young people have to say!🌟 #DeepSeek #AI #China ChitChat China🇨🇳🇺🇸 薛剑XueJian 顾昭岳 Zhang Heqing Zhang Meifang
5:24

GenZ Pop Quiz🔬 | DeepSeek Leads the AI Wave: Career Challenges or Blue Ocean of Opportunities? Chinese tech companies like DeepSeek are making a massive splash on the world stage, totally redefining China's place in the global tech scene. Chinese AI isn't just a wave—it's a tidal wave! But what does this mean for us? Are we facing a career challenge or diving into a sea of opportunities? Let's find out what China's young people have to say!🌟 #DeepSeek #AI #China ChitChat China🇨🇳🇺🇸 薛剑XueJian 顾昭岳 Zhang Heqing Zhang Meifang

Journey Album GBA

523,204 просмотров • 1 год назад

🇨🇳 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 просмотров • 1 месяц назад

JENSEN HUANG: THE AMERICAN TECH STACK IS HOW WE WIN THE AI RACE "DeepSeek when it came out, it was a great win for the United States. Imagine if DeepSeek came out and only ran on Huawei. The fact of the matter is American tech stack all over the world being the world's standard is vital to the future of winning the AI race. You can't do it any other way, as you know, any computing platform wins because of developers, and half of the world's developers are in China." Source: The All-In Podcast
0:39

JENSEN HUANG: THE AMERICAN TECH STACK IS HOW WE WIN THE AI RACE "DeepSeek when it came out, it was a great win for the United States. Imagine if DeepSeek came out and only ran on Huawei. The fact of the matter is American tech stack all over the world being the world's standard is vital to the future of winning the AI race. You can't do it any other way, as you know, any computing platform wins because of developers, and half of the world's developers are in China." Source: The All-In Podcast

Mario Nawfal

45,238 просмотров • 1 год назад

HERMES DESKTOP APP JUST GOT A NEW ULTRA MODE FOR DEEPSEEK V4 PRO – AND IT COSTS ABOUT $1 A DAY TO RUN If you're using Hermes desktop app, you're probably already running DeepSeek – it's one of the top models available. The update: → DeepSeek V4 Pro now has thinking mode, fast mode, and a brand new ultra mode → There's also an extra high mode, but the real upgrade is ultra The actual cost: roughly $1/day for a normal workflow. That's about $20-25/month – basically the same as before, just with a significantly faster mode unlocked. The verdict after a full day of testing: it flies through tool calling. Noticeably faster, same price range. If you're already paying for DeepSeek through Hermes, this is a free upgrade sitting in your settings right now. Update Hermes, grab the DeepSeek API if you don't have it yet, and try V4 Pro on ultra. Bookmark this, you'll want to come back to it later.
1:00

HERMES DESKTOP APP JUST GOT A NEW ULTRA MODE FOR DEEPSEEK V4 PRO – AND IT COSTS ABOUT $1 A DAY TO RUN If you're using Hermes desktop app, you're probably already running DeepSeek – it's one of the top models available. The update: → DeepSeek V4 Pro now has thinking mode, fast mode, and a brand new ultra mode → There's also an extra high mode, but the real upgrade is ultra The actual cost: roughly $1/day for a normal workflow. That's about $20-25/month – basically the same as before, just with a significantly faster mode unlocked. The verdict after a full day of testing: it flies through tool calling. Noticeably faster, same price range. If you're already paying for DeepSeek through Hermes, this is a free upgrade sitting in your settings right now. Update Hermes, grab the DeepSeek API if you don't have it yet, and try V4 Pro on ultra. Bookmark this, you'll want to come back to it later.

SCOTTY BEAM

24,032 просмотров • 15 дней назад

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 просмотров • 1 год назад

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 просмотров • 1 месяц назад

🇨🇳 🇺🇸 CHINA JUST LANDED ANOTHER BLOW ON THE US STORAGE CARTEL. Huawei is closing the gap on Samsung without access to American tech. Samsung stacks storage chips up to 400+ layers high, the most advanced in the world. Huawei has been banned from buying that tech since 2019. China's best domestic alternative tops out at 232 layers, almost half the density. So Huawei stopped trying to win the layer race. Instead they invented a new way to pack chips onto the circuit board itself. More chips, smaller footprint, none of the expensive packaging. The result: a 122TB AI storage drive that nearly matches Samsung's flagship. Built with inferior chips. Cheaper to produce. A 245TB version is already in the pipeline. Every export ban produces a domestic workaround. Every restriction funnels more revenue into Chinese chipmakers, who reinvest it into closing the gap. Washington wanted to slow China down. Instead it forced them to innovate.
0:20

🇨🇳 🇺🇸 CHINA JUST LANDED ANOTHER BLOW ON THE US STORAGE CARTEL. Huawei is closing the gap on Samsung without access to American tech. Samsung stacks storage chips up to 400+ layers high, the most advanced in the world. Huawei has been banned from buying that tech since 2019. China's best domestic alternative tops out at 232 layers, almost half the density. So Huawei stopped trying to win the layer race. Instead they invented a new way to pack chips onto the circuit board itself. More chips, smaller footprint, none of the expensive packaging. The result: a 122TB AI storage drive that nearly matches Samsung's flagship. Built with inferior chips. Cheaper to produce. A 245TB version is already in the pipeline. Every export ban produces a domestic workaround. Every restriction funnels more revenue into Chinese chipmakers, who reinvest it into closing the gap. Washington wanted to slow China down. Instead it forced them to innovate.

CryptoGoos

563,358 просмотров • 2 месяцев назад

🚨🇺🇸🇨🇳 MICROSOFT & OPENAI SUSPECT DEEPSEEK OF “BORROWING” THEIR TECH Microsoft and OpenAI are investigating whether DeepSeek, a Chinese AI startup, helped itself to OpenAI’s data using its API. Microsoft’s security team flagged suspicious large-scale data extraction in late 2023, suggesting DeepSeek may have sneakily bypassed restrictions to grab more than it paid for. Not-so-coincidentally, DeepSeek just dropped “R1,” an AI model that supposedly rivals OpenAI, Google, and Meta—at a fraction of the cost. The news sent tech stocks into meltdown mode, erasing nearly $1 trillion from companies like Microsoft, Nvidia, Oracle, and Google. Investors weren’t thrilled about a potential AI leapfrogging moment. Trump’s AI czar David Sacks: "There’s substantial evidence that what DeepSeek did here is they distilled knowledge out of OpenAI models and I don’t think OpenAI is very happy about this.” OpenAI isn’t naming names but warns China is constantly trying to siphon off US AI tech and says it’s working with the US government to lock things down. Source: Bloomberg Media Source: Reuters
1:23

🚨🇺🇸🇨🇳 MICROSOFT & OPENAI SUSPECT DEEPSEEK OF “BORROWING” THEIR TECH Microsoft and OpenAI are investigating whether DeepSeek, a Chinese AI startup, helped itself to OpenAI’s data using its API. Microsoft’s security team flagged suspicious large-scale data extraction in late 2023, suggesting DeepSeek may have sneakily bypassed restrictions to grab more than it paid for. Not-so-coincidentally, DeepSeek just dropped “R1,” an AI model that supposedly rivals OpenAI, Google, and Meta—at a fraction of the cost. The news sent tech stocks into meltdown mode, erasing nearly $1 trillion from companies like Microsoft, Nvidia, Oracle, and Google. Investors weren’t thrilled about a potential AI leapfrogging moment. Trump’s AI czar David Sacks: "There’s substantial evidence that what DeepSeek did here is they distilled knowledge out of OpenAI models and I don’t think OpenAI is very happy about this.” OpenAI isn’t naming names but warns China is constantly trying to siphon off US AI tech and says it’s working with the US government to lock things down. Source: Bloomberg Media Source: Reuters

Mario Nawfal

822,553 просмотров • 1 год назад

How does the U.S. win the AI race without tightening export controls on advanced AI chips to China? NVIDIA CEO: • China will not base its defense on Western tech • The Pentagon doesn’t use Chinese chips • China has domestic AI chips (Huawei, startups) and manufactures at scale, so its military has access • The U.S. needs a nuanced plan to stay ahead • Make the American tech stack the global standard • If others can’t build on the American stack, they’ll build on another stack • KPI David Sacks 5y → 80% = win; 20% = loss • China: 50% of AI researchers, 30% of the tech market, ~1B users • Cost of isolation: forfeits ~30% of the market, blocks diffusion of U.S. tech, concedes the rest of the world • President Trump wouldn’t view isolation as a winning strategy To win the AI race, the U.S. must lead with the best chips—and win developers and markets worldwide.
2:32

How does the U.S. win the AI race without tightening export controls on advanced AI chips to China? NVIDIA CEO: • China will not base its defense on Western tech • The Pentagon doesn’t use Chinese chips • China has domestic AI chips (Huawei, startups) and manufactures at scale, so its military has access • The U.S. needs a nuanced plan to stay ahead • Make the American tech stack the global standard • If others can’t build on the American stack, they’ll build on another stack • KPI David Sacks 5y → 80% = win; 20% = loss • China: 50% of AI researchers, 30% of the tech market, ~1B users • Cost of isolation: forfeits ~30% of the market, blocks diffusion of U.S. tech, concedes the rest of the world • President Trump wouldn’t view isolation as a winning strategy To win the AI race, the U.S. must lead with the best chips—and win developers and markets worldwide.

Ask Perplexity

156,952 просмотров • 9 месяцев назад

🚨 THIS IS EXTREMELY BAD FOR $NVDA. China is preparing a $295 billion plan to build AI data centers across the whole country. The catch for America: at least 80% of the chips must be homegrown. That means Huawei in. Nvidia out. Jensen Huang confirmed this last month. Nvidia has "largely conceded" China to Huawei, he told CNBC. China once accounted for at least 20% of Nvidia's entire data center revenue. That market is now all but GONE. America spent years locking China out. China just stopped knocking.
0:20

🚨 THIS IS EXTREMELY BAD FOR $NVDA. China is preparing a $295 billion plan to build AI data centers across the whole country. The catch for America: at least 80% of the chips must be homegrown. That means Huawei in. Nvidia out. Jensen Huang confirmed this last month. Nvidia has "largely conceded" China to Huawei, he told CNBC. China once accounted for at least 20% of Nvidia's entire data center revenue. That market is now all but GONE. America spent years locking China out. China just stopped knocking.

CryptoGoos

187,403 просмотров • 1 месяц назад

Google just had its DeepSeek moment — and almost nobody's talking about it. Here's the story you need to know. 🧵 When DeepSeek dropped in early 2025, it didn't just impress people. It scared them. A model competing with the biggest AI players — at a fraction of the cost — through math, not hardware. Chip stocks tanked. The industry panicked. Then on March 24th, 2026, Google published a research paper called TurboQuant. Cloudflare's CEO immediately called it Google's DeepSeek moment. Memory chip stocks for Micron and Western Digital fell on the news. Why? Because TurboQuant compresses AI memory by 6x — through software alone. → No new chips needed → No retraining required → One server can now host more models than before The era of throwing hardware at AI problems is ending. The era of mathematical efficiency is here. ✅Save this post, you'll thank yourself when this reshapes every AI tool you use. 📌 Want the SOP? DM me.
8:21

Google just had its DeepSeek moment — and almost nobody's talking about it. Here's the story you need to know. 🧵 When DeepSeek dropped in early 2025, it didn't just impress people. It scared them. A model competing with the biggest AI players — at a fraction of the cost — through math, not hardware. Chip stocks tanked. The industry panicked. Then on March 24th, 2026, Google published a research paper called TurboQuant. Cloudflare's CEO immediately called it Google's DeepSeek moment. Memory chip stocks for Micron and Western Digital fell on the news. Why? Because TurboQuant compresses AI memory by 6x — through software alone. → No new chips needed → No retraining required → One server can now host more models than before The era of throwing hardware at AI problems is ending. The era of mathematical efficiency is here. ✅Save this post, you'll thank yourself when this reshapes every AI tool you use. 📌 Want the SOP? DM me.

Julian Goldie SEO

12,731 просмотров • 4 месяцев назад

Here's my 5-hour conversation with Dylan Patel and Nathan Lambert on DeepSeek, China, OpenAI, NVIDIA, xAI, Google, Anthropic, Meta, Microsoft, TSMC, Stargate, megacluster buildouts, RL, reasoning, and a lot of other topics at the cutting edge of AI. This is was a mind-blowing, super-technical, and fun conversation. Yes, we discuss r1 and o3-mini, but more importantly we look into the future of technology, geopolitics, and humanity in a world that stands on the precipice of a global AI revolution. The first 4 hours are here on X (4 hours is current limit), and the full 5 hours are up everywhere else. Links in comment. Timestamps: 0:00 - Introduction 3:33 - DeepSeek-R1 and DeepSeek-V3 25:07 - Low cost of training 51:25 - DeepSeek compute cluster 58:57 - Export controls on GPUs to China 1:09:16 - AGI timeline 1:18:41 - China's manufacturing capacity 1:26:36 - Cold war with China 1:31:05 - TSMC and Taiwan 1:54:44 - Best GPUs for AI 2:09:36 - Why DeepSeek is so cheap 2:22:55 - Espionage 2:31:57 - Censorship 2:44:52 - Andrej Karpathy and magic of RL 2:55:23 - OpenAI o3-mini vs DeepSeek r1 3:14:31 - NVIDIA 3:18:58 - GPU smuggling 3:25:36 - DeepSeek training on OpenAI data 3:36:04 - AI megaclusters 4:11:26 - Who wins the race to AGI? 4:21:39 - AI agents 4:30:21 - Programming and AI 4:37:49 - Open source 4:47:01 - Stargate 4:54:30 - Future of AI
3:59:56

Here's my 5-hour conversation with Dylan Patel and Nathan Lambert on DeepSeek, China, OpenAI, NVIDIA, xAI, Google, Anthropic, Meta, Microsoft, TSMC, Stargate, megacluster buildouts, RL, reasoning, and a lot of other topics at the cutting edge of AI. This is was a mind-blowing, super-technical, and fun conversation. Yes, we discuss r1 and o3-mini, but more importantly we look into the future of technology, geopolitics, and humanity in a world that stands on the precipice of a global AI revolution. The first 4 hours are here on X (4 hours is current limit), and the full 5 hours are up everywhere else. Links in comment. Timestamps: 0:00 - Introduction 3:33 - DeepSeek-R1 and DeepSeek-V3 25:07 - Low cost of training 51:25 - DeepSeek compute cluster 58:57 - Export controls on GPUs to China 1:09:16 - AGI timeline 1:18:41 - China's manufacturing capacity 1:26:36 - Cold war with China 1:31:05 - TSMC and Taiwan 1:54:44 - Best GPUs for AI 2:09:36 - Why DeepSeek is so cheap 2:22:55 - Espionage 2:31:57 - Censorship 2:44:52 - Andrej Karpathy and magic of RL 2:55:23 - OpenAI o3-mini vs DeepSeek r1 3:14:31 - NVIDIA 3:18:58 - GPU smuggling 3:25:36 - DeepSeek training on OpenAI data 3:36:04 - AI megaclusters 4:11:26 - Who wins the race to AGI? 4:21:39 - AI agents 4:30:21 - Programming and AI 4:37:49 - Open source 4:47:01 - Stargate 4:54:30 - Future of AI

Lex Fridman

1,154,101 просмотров • 1 год назад

🚨 CHINA'S AI PLAYBOOK ISN'T TO BEAT OPENAI AND ANTHROPIC. IT'S TO MAKE THEM IRRELEVANT BY MAKING INTELLIGENCE FREE. Chinese labs are giving away frontier-level models for free. Zhipu's GLM-5 already beats Claude Opus 4.5 and Gemini 3.0 Pro on key benchmarks. DeepSeek, Qwen, and Kimi round out 4 of the top 5 open-weight models globally, all released under open licenses anyone can use commercially. The real weapon isn't the models, it's the cost to run them. Chinese provinces like Gansu, Guizhou, and Inner Mongolia are cutting data center power bills by up to 50%. DeepSeek trained its R1 model for around $6 million, compared to roughly $100 million for GPT-4. The remaining blocker is chips. US export controls still cut China off from Nvidia's best hardware. But Zhipu already trained a full frontier model entirely on Huawei's Ascend chips, no Nvidia involved. Huawei's next-gen Atlas 950 cluster, launching late 2026, claims 6.7 times the compute of Nvidia's planned NVL144 systems. If Huawei closes the chip gap while China keeps giving away free, near frontier models running on subsidized power. The entire business model OpenAI and Anthropic are built on, charging hundreds of billions in aggregate revenue for access to intelligence, stops making sense. Why pay premium prices for marginal capability gains when a free alternative running on cheap compute gets you 90% of the way there.
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🚨 CHINA'S AI PLAYBOOK ISN'T TO BEAT OPENAI AND ANTHROPIC. IT'S TO MAKE THEM IRRELEVANT BY MAKING INTELLIGENCE FREE. Chinese labs are giving away frontier-level models for free. Zhipu's GLM-5 already beats Claude Opus 4.5 and Gemini 3.0 Pro on key benchmarks. DeepSeek, Qwen, and Kimi round out 4 of the top 5 open-weight models globally, all released under open licenses anyone can use commercially. The real weapon isn't the models, it's the cost to run them. Chinese provinces like Gansu, Guizhou, and Inner Mongolia are cutting data center power bills by up to 50%. DeepSeek trained its R1 model for around $6 million, compared to roughly $100 million for GPT-4. The remaining blocker is chips. US export controls still cut China off from Nvidia's best hardware. But Zhipu already trained a full frontier model entirely on Huawei's Ascend chips, no Nvidia involved. Huawei's next-gen Atlas 950 cluster, launching late 2026, claims 6.7 times the compute of Nvidia's planned NVL144 systems. If Huawei closes the chip gap while China keeps giving away free, near frontier models running on subsidized power. The entire business model OpenAI and Anthropic are built on, charging hundreds of billions in aggregate revenue for access to intelligence, stops making sense. Why pay premium prices for marginal capability gains when a free alternative running on cheap compute gets you 90% of the way there.

The Macro Paper

71,691 просмотров • 1 месяц назад

🚨 🇨🇳 🇺🇸 HUAWEI'S CHAIRMAN JUST THANKED THE US FOR ITS CHIP SANCTIONS. His message: the export controls didn't cripple Huawei. They forced it to build everything itself. It made the company stronger than ever. The US cut Huawei off in 2019. So Huawei went into "extreme survival mode" and designed 381 chips from scratch in six years, leading to the LogicFolding breakthrough. Now even Jensen Huang admits $NVDA has "largely conceded" China's AI chip market to Huawei. The sanctions meant to stop China's chip industry are the exact reason it exists today. America tried to deny them the tools. So China built their own. That is how empires accidentally create their successors.
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🚨 🇨🇳 🇺🇸 HUAWEI'S CHAIRMAN JUST THANKED THE US FOR ITS CHIP SANCTIONS. His message: the export controls didn't cripple Huawei. They forced it to build everything itself. It made the company stronger than ever. The US cut Huawei off in 2019. So Huawei went into "extreme survival mode" and designed 381 chips from scratch in six years, leading to the LogicFolding breakthrough. Now even Jensen Huang admits $NVDA has "largely conceded" China's AI chip market to Huawei. The sanctions meant to stop China's chip industry are the exact reason it exists today. America tried to deny them the tools. So China built their own. That is how empires accidentally create their successors.

CryptoGoos

19,426 просмотров • 2 месяцев назад

🚨 BREAKING 🇨🇳🇺🇸 CHINA JUST COMPLETELY BANNED NVIDIA CHIPS BEIJING HAS CANCELED THE GREEN LIGHT FOR TOP CHINESE COMPANIES TO BUY $NVDA CHIPS THE MESSAGE IS CLEAR CHINA DOES NOT WANT TO DEPEND ON U.S. SEMICONDUCTORS ANYMORE THEY WOULD RATHER BUILD THEIR OWN AI SUPPLY CHAIN THAN BUY FROM AMERICA THIS IS NOT JUST ABOUT NVIDIA THIS IS ABOUT CHINA CUTTING THE U.S. OUT OF ITS AI FUTURE $NVDA IS GETTING HIT HARD AND THE TRADE WAR JUST ENTERED A NEW PHASE
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🚨 BREAKING 🇨🇳🇺🇸 CHINA JUST COMPLETELY BANNED NVIDIA CHIPS BEIJING HAS CANCELED THE GREEN LIGHT FOR TOP CHINESE COMPANIES TO BUY $NVDA CHIPS THE MESSAGE IS CLEAR CHINA DOES NOT WANT TO DEPEND ON U.S. SEMICONDUCTORS ANYMORE THEY WOULD RATHER BUILD THEIR OWN AI SUPPLY CHAIN THAN BUY FROM AMERICA THIS IS NOT JUST ABOUT NVIDIA THIS IS ABOUT CHINA CUTTING THE U.S. OUT OF ITS AI FUTURE $NVDA IS GETTING HIT HARD AND THE TRADE WAR JUST ENTERED A NEW PHASE

Leshka.eth ⛩

102,073 просмотров • 23 дней назад

🇨🇳🇺🇸 ELON: CHINA HAS IMMENSE TALENT, BUT DEEPSEEK IS NOT AN AI REVOLUTION “There are a lot of very smart and very motivated engineers in China, and you should expect that China will come up with many great things. For most of human history, China has been the most powerful nation on earth, so they see their rise as a return to normal. DeepSeek is impressive, but it’s not a complete revolution in AI—xAI and others will soon release better models.” Source: Tsarathustra
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🇨🇳🇺🇸 ELON: CHINA HAS IMMENSE TALENT, BUT DEEPSEEK IS NOT AN AI REVOLUTION “There are a lot of very smart and very motivated engineers in China, and you should expect that China will come up with many great things. For most of human history, China has been the most powerful nation on earth, so they see their rise as a return to normal. DeepSeek is impressive, but it’s not a complete revolution in AI—xAI and others will soon release better models.” Source: Tsarathustra

Mario Nawfal

1,068,377 просмотров • 9 месяцев назад

I'm running Llama 4 Maverick at 620 t/s! I'm living in the future! Honestly, a large language model running this fast is something straight out of a sci-fi movie. Speeds like this will enable a whole new world of applications that aren't possible today. For reference, GPT-4o, which is probably the most popular OpenAI model, runs between 60 and 110 t/s. The secret here: I'm not running AI at Meta's Llama 4 Maverick on a GPU. I'm using the SambaNova Cloud (my sponsor) and their custom SN40L chips. They are optimized from the ground up for running AI workflows. Right now, SambaNova Cloud runs DeepSeek, Qwen, Whisper, and the entire family of Llama models on these chips. You can check the speed of each of these models using SambaNova Cloud's Playground (see the attached video). It's completely free, and that's how I'm measuring their speeds. For example, I also tried DeepSeek R1 (the latest version from May) and, oh boy! DeepSeek R1 is a huge 671B parameter model. It's probably the best open reasoning model in the world, and it runs at 140 tokens per second! !!! Inference time on an SN40L is night and day from what you'll get from a GPU. Here is why this is big: If you are running an agentic workflow that uses multiple models simultaneously on a GPU, it will need to swap models in and out of memory (because not every model fits). A single SNL40 chip can simultaneously hold over 100 models (trillions of parameters) in memory. If you are using open models, try the SambaCloud API to see what lightning speed looks like. Here is how: 1. Create a free account at: 2. Check the QuickStart guide: If you try the playground, check the speed you're getting with Llama 4 and DeepSeek, and post the results below. I've seen much higher numbers than I posted here, so I'm curious to see whether geography affects the speed.
1:10

I'm running Llama 4 Maverick at 620 t/s! I'm living in the future! Honestly, a large language model running this fast is something straight out of a sci-fi movie. Speeds like this will enable a whole new world of applications that aren't possible today. For reference, GPT-4o, which is probably the most popular OpenAI model, runs between 60 and 110 t/s. The secret here: I'm not running AI at Meta's Llama 4 Maverick on a GPU. I'm using the SambaNova Cloud (my sponsor) and their custom SN40L chips. They are optimized from the ground up for running AI workflows. Right now, SambaNova Cloud runs DeepSeek, Qwen, Whisper, and the entire family of Llama models on these chips. You can check the speed of each of these models using SambaNova Cloud's Playground (see the attached video). It's completely free, and that's how I'm measuring their speeds. For example, I also tried DeepSeek R1 (the latest version from May) and, oh boy! DeepSeek R1 is a huge 671B parameter model. It's probably the best open reasoning model in the world, and it runs at 140 tokens per second! !!! Inference time on an SN40L is night and day from what you'll get from a GPU. Here is why this is big: If you are running an agentic workflow that uses multiple models simultaneously on a GPU, it will need to swap models in and out of memory (because not every model fits). A single SNL40 chip can simultaneously hold over 100 models (trillions of parameters) in memory. If you are using open models, try the SambaCloud API to see what lightning speed looks like. Here is how: 1. Create a free account at: 2. Check the QuickStart guide: If you try the playground, check the speed you're getting with Llama 4 and DeepSeek, and post the results below. I've seen much higher numbers than I posted here, so I'm curious to see whether geography affects the speed.

Santiago

34,148 просмотров • 1 год назад