Загрузка видео...

Не удалось загрузить видео

На главную

SITUATION EXPLAINED: Why is China building a sovereign AI stack to compete with Nvidia? We asked Glinert 🇺🇸 🏭 and Mitchell Nahmias, co-founders of Sphere Semi. "What I see as the only real viable crack in Nvidia's armor is what's coming out of China, which is ironic given Jensen's...

MTSlive's profile picture

MTS

256,936 subscribers

26,278 просмотров • 18 дней назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Ingraham: Trump announced he's lifting some export controls on Nvidia allowing the chip maker to sell some products to approved customers in China. Why are we giving anything to China? Johnson: I met with Jenson, the CEO of Nvidia and the way he explains is he has about 95% market share effectively of AI. And with the chips and everything that is involved in that, his argument is if he's not able to compete in China, their system can over take him and thus the U.S.
1:38

Ingraham: Trump announced he's lifting some export controls on Nvidia allowing the chip maker to sell some products to approved customers in China. Why are we giving anything to China? Johnson: I met with Jenson, the CEO of Nvidia and the way he explains is he has about 95% market share effectively of AI. And with the chips and everything that is involved in that, his argument is if he's not able to compete in China, their system can over take him and thus the U.S.

Acyn

133,311 просмотров • 7 месяцев назад

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.
1:42

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

🚨🇺🇸🇨🇳 SPEAKER JOHNSON DEFENDS TRUMP SELLING NVIDIA AI CHIPS TO CHINA: "IF WE DON'T, THEY'LL OVERTAKE US" Speaker Johnson explained Trump's decision to lift export controls allowing Nvidia to sell AI chips to approved Chinese customers, warning that blocking sales could allow China to overtake America's AI dominance: "China is a principal threat except for the national debt. I met with Jensen, the CEO of Nvidia. He has about 95% market share of AI. His argument is if he's not able to compete in China, then their system can overtake him and thus overtake the US. It's a delicate balance. We've got to treat China as the adversary that they are but also they're a really important trade partner." Source: Fox
1:31

🚨🇺🇸🇨🇳 SPEAKER JOHNSON DEFENDS TRUMP SELLING NVIDIA AI CHIPS TO CHINA: "IF WE DON'T, THEY'LL OVERTAKE US" Speaker Johnson explained Trump's decision to lift export controls allowing Nvidia to sell AI chips to approved Chinese customers, warning that blocking sales could allow China to overtake America's AI dominance: "China is a principal threat except for the national debt. I met with Jensen, the CEO of Nvidia. He has about 95% market share of AI. His argument is if he's not able to compete in China, then their system can overtake him and thus overtake the US. It's a delicate balance. We've got to treat China as the adversary that they are but also they're a really important trade partner." Source: Fox

Mario Nawfal

28,949 просмотров • 7 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."
1:53

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

910,407 просмотров • 1 год назад

Zuck: "The export controls are clearly working in a way. DeepSeek did all these very impressive low-level optimizations. That is impressive. But then you ask: why did they have to do that when none of the American labs did? Well, because they're using partially nerfed chips—that are the only thing that Nvidia is allowed to sell in China because of the export controls."
1:16

Zuck: "The export controls are clearly working in a way. DeepSeek did all these very impressive low-level optimizations. That is impressive. But then you ask: why did they have to do that when none of the American labs did? Well, because they're using partially nerfed chips—that are the only thing that Nvidia is allowed to sell in China because of the export controls."

Dwarkesh Patel

361,585 просмотров • 1 год 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

187,063 просмотров • 1 месяц назад

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

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

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

234,773 просмотров • 2 месяцев назад

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

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

Karl Mehta

14,946 просмотров • 14 дней назад

Prof. Jeffrey Sachs: "China🇨🇳 was supposed to develop in a way that is subservient to the United States🇺🇸 (they didn’t)…now they have to be punished.” A reminder as Trump visits China that the entire US’ mounting pressure against Beijing for a coming war is because not only did China develop in a way that wasn’t subservient to Washington, like Japan… But China also built a better economic system, which is obvious to Americans and the rest of the world. The US wants to weaken China to stop Americans asking ‘why can’t we live like that?’ or ‘why can we not have that infrastructure here?’
1:17

Prof. Jeffrey Sachs: "China🇨🇳 was supposed to develop in a way that is subservient to the United States🇺🇸 (they didn’t)…now they have to be punished.” A reminder as Trump visits China that the entire US’ mounting pressure against Beijing for a coming war is because not only did China develop in a way that wasn’t subservient to Washington, like Japan… But China also built a better economic system, which is obvious to Americans and the rest of the world. The US wants to weaken China to stop Americans asking ‘why can’t we live like that?’ or ‘why can we not have that infrastructure here?’

Afshin Rattansi

124,826 просмотров • 2 месяцев назад

🚨🚨🚨BREAKING: Nvidia CEO was just asked about his thoughts on Huawei and China > Huawei is one of the most formidable technology companies in the world. > they are incredible in computing, networking technology and software capabilities > they have all the essential capabilities to advance AI > China is right behind the US in AI > 50% of the world’s AI researchers are chinese The race is on.
1:20

🚨🚨🚨BREAKING: Nvidia CEO was just asked about his thoughts on Huawei and China > Huawei is one of the most formidable technology companies in the world. > they are incredible in computing, networking technology and software capabilities > they have all the essential capabilities to advance AI > China is right behind the US in AI > 50% of the world’s AI researchers are chinese The race is on.

NIK

585,511 просмотров • 1 год назад

NVIDIA CEO: “CHINA IS MOVING INCREDIBLY FAST IN AI” Jensen Huang said China is accelerating AI on all fronts - infrastructure, models, and real-world applications: "China is fast to both invent a new technology, but also to integrate the technology, to apply the technology. And because there's so much competition in China, everybody wants to build a great company and wants to succeed, a lot of great capabilities come out. And at the foundation of all of that is China's education system has produced some of the world's finest AI researchers - about 50% of the world's AI researchers are based here in China." Source:
1:40

NVIDIA CEO: “CHINA IS MOVING INCREDIBLY FAST IN AI” Jensen Huang said China is accelerating AI on all fronts - infrastructure, models, and real-world applications: "China is fast to both invent a new technology, but also to integrate the technology, to apply the technology. And because there's so much competition in China, everybody wants to build a great company and wants to succeed, a lot of great capabilities come out. And at the foundation of all of that is China's education system has produced some of the world's finest AI researchers - about 50% of the world's AI researchers are based here in China." Source:

Mario Nawfal

1,018,768 просмотров • 1 год 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

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.
1:01

Nvidia is pulling off the most sophisticated financial loop in tech history. They invested $40 BILLION in its own customers in just 5 months. Here's why this could blow up the entire AI economy: Nvidia generated $97 billion in free cash flow last year. Instead of sitting on it, Jensen started writing checks to every company in the AI supply chain. Not small checks. We're talking about billions at a time. And almost every single one of those companies turns around and spends that money on Nvidia chips. Follow the money: $30 billion into OpenAI. OpenAI is one of Nvidia's largest GPU customers and spends billions annually on Nvidia hardware through cloud providers. $2 billion into CoreWeave, a company that exists exclusively to rent out data centers full of Nvidia GPUs. $2 billion into Marvell for silicon photonics that connects Nvidia systems. $2 billion into Lumentum for optical tech that powers Nvidia data centers. $2 billion into Coherent for the same thing. $2 billion into Nebius, an AI cloud company deploying Nvidia infrastructure. $3.2 billion into Corning, the glassmaker building three new US factories specifically to make fiber optic cables for Nvidia's next-gen systems. $2.1 billion into IREN, a data center operator that just agreed to deploy 5 gigawatts of Nvidia-designed infrastructure. And the list goes on. Every single recipient either buys Nvidia chips directly, builds infrastructure that runs on Nvidia chips, or manufactures components that go inside Nvidia systems. Matthew Bryson, an analyst at Wedbush Securities, said in a research note that Nvidia's dealmaking fits "squarely into the circular investment theme." Bloomberg even published an entire interactive feature this week titled "AI Circular Deals: How Microsoft, OpenAI and Nvidia Keep Paying Each Other." The piece maps how capital flows between the same handful of companies and gets counted as revenue multiple times along the way. But here's the part that makes this genuinely complicated: Nvidia's $5 billion investment in Intel from September is now worth over $25 billion. That's a 5x return in months. Their private company portfolio went from $3.4 billion to $22.3 billion on the balance sheet in a single year. They booked $8.9 billion in gains from equity investments alone. So when critics say "circular investing," Nvidia can point to Intel and say "we turned $5 billion into $25 billion, this is just smart capital deployment." And they're not wrong. Some of these bets ARE paying off like crazy. The real question is whether Nvidia is a chipmaker that happens to invest, or a venture fund that happens to sell chips. Because right now Jensen is doing both at a scale that has never existed in the semiconductor industry. No chipmaker in history has EVER invested $40 billion in its own ecosystem in five months. Last fiscal year Nvidia invested $17.5 billion in private companies. Their SEC filing literally says those investments include "AI model companies that purchase its products directly or through cloud service providers." They're saying it themselves: We invest in companies that buy our products. On Nvidia's last earnings call, Jensen told investors their investments are focused on "expanding and deepening our ecosystem reach." Translate that from CEO-speak and it means " we're funding the companies that fund us. The bull case says Nvidia is building an unbreakable moat by financing the entire AI supply chain and ensuring it all runs on Nvidia hardware. The bear case says this is the most elaborate circular revenue scheme since the subprime mortgage era and it all breaks apart the moment one domino falls. Both cases use the exact same evidence.

Ricardo

159,113 просмотров • 2 месяцев назад

We asked (Co-Founder & CEO, webAI) about the advantages of running AI on devices. "There's no free lunch, but there are things cloud players can't do. It's RAM intensive, yes, but by distributing across devices, we can unlock more accuracy and context. But if you're hosting for a million users on Nvidia, you can't do that." "With our stack, everything's downstream only. Think about health data, like you want that to be private. The dream is personalized models for millions that never leave their device."
1:19

We asked (Co-Founder & CEO, webAI) about the advantages of running AI on devices. "There's no free lunch, but there are things cloud players can't do. It's RAM intensive, yes, but by distributing across devices, we can unlock more accuracy and context. But if you're hosting for a million users on Nvidia, you can't do that." "With our stack, everything's downstream only. Think about health data, like you want that to be private. The dream is personalized models for millions that never leave their device."

TBPN

10,084 просмотров • 11 месяцев назад

Earlier this year we announced that telecom leaders are building AI grids using NVIDIA AI infrastructure to optimize inference on distributed networks But what actually is an AI Grid? In this video, Amogh Dendukuri takes us back to basics. Watch now to see him break down the top 5 things you need to know about AI grids.
2:23

Earlier this year we announced that telecom leaders are building AI grids using NVIDIA AI infrastructure to optimize inference on distributed networks But what actually is an AI Grid? In this video, Amogh Dendukuri takes us back to basics. Watch now to see him break down the top 5 things you need to know about AI grids.

NVIDIA

27,166 просмотров • 1 месяц назад

THAT MOMENT WHEN NVIDIA CEO JENSEN HUANG WAS ASKED ABOUT HIS COMMENTS ON CHINA BEATING THE U.S. IN THE AI RACE: “THAT’S NOT WHAT I SAID. WHAT I SAID WAS THAT CHINA HAS VERY GOOD AI TECHNOLOGY. THEY HAVE MANY AI RESEARCHERS. IN FACT, 50% OF THE WORLD’S AI RESEARCHERS ARE IN CHINA. THEY DEVELOP VERY GOOD AI TECHNOLOGY. THE MOST POPULAR OPEN-SOURCE AI MODELS IN THE WORLD TODAY ARE FROM CHINA. SO THEY ARE MOVING VERY, VERY FAST. THE UNITED STATES HAS TO CONTINUE TO MOVE INCREDIBLY FAST. OTHERWISE, THE WORLD IS VERY COMPETITIVE, SO WE HAVE TO RUN FAST.”
0:40

THAT MOMENT WHEN NVIDIA CEO JENSEN HUANG WAS ASKED ABOUT HIS COMMENTS ON CHINA BEATING THE U.S. IN THE AI RACE: “THAT’S NOT WHAT I SAID. WHAT I SAID WAS THAT CHINA HAS VERY GOOD AI TECHNOLOGY. THEY HAVE MANY AI RESEARCHERS. IN FACT, 50% OF THE WORLD’S AI RESEARCHERS ARE IN CHINA. THEY DEVELOP VERY GOOD AI TECHNOLOGY. THE MOST POPULAR OPEN-SOURCE AI MODELS IN THE WORLD TODAY ARE FROM CHINA. SO THEY ARE MOVING VERY, VERY FAST. THE UNITED STATES HAS TO CONTINUE TO MOVE INCREDIBLY FAST. OTHERWISE, THE WORLD IS VERY COMPETITIVE, SO WE HAVE TO RUN FAST.”

Vivek Sen

155,572 просмотров • 1 месяц назад

AI investment is expanding beyond models and applications into the full stack that supports them. Energy capacity, semiconductor supply, compute infrastructure, and software layers are becoming more connected, influencing how and where AI can be built and deployed. In partnership with NVIDIA, The Futurum Group examines the Five Layers of the AI Cake framework as a way to understand the structure of the AI economy. The market brief outlines how value is distributed across the stack, where bottlenecks are forming, and what these dynamics mean for enterprise strategy, capital allocation, workforce planning, and global competitiveness. ⏯️ Explore the key findings, and use the link to download the full report: 👉 #AIInfrastructure #NVIDIA #Futurum
1:12

AI investment is expanding beyond models and applications into the full stack that supports them. Energy capacity, semiconductor supply, compute infrastructure, and software layers are becoming more connected, influencing how and where AI can be built and deployed. In partnership with NVIDIA, The Futurum Group examines the Five Layers of the AI Cake framework as a way to understand the structure of the AI economy. The market brief outlines how value is distributed across the stack, where bottlenecks are forming, and what these dynamics mean for enterprise strategy, capital allocation, workforce planning, and global competitiveness. ⏯️ Explore the key findings, and use the link to download the full report: 👉 #AIInfrastructure #NVIDIA #Futurum

The Futurum Group

75,859 просмотров • 2 месяцев назад

Elon Musk on where people should invest: "I don't really buy stocks. I don't look for things to invest in. I just try to build things and then there happens to be stock of the company that I built, but I don't have like a portfolio or anything; Google is gonna be pretty valuable in the future. They've laid the ground work for an immense amount of value creation from an AI standpoint. Nvidia is obvious at this point. There's an argument that companies that do AI and robotics, and maybe spaceflight, are going to be overwhelmingly almost all of the value."
1:29

Elon Musk on where people should invest: "I don't really buy stocks. I don't look for things to invest in. I just try to build things and then there happens to be stock of the company that I built, but I don't have like a portfolio or anything; Google is gonna be pretty valuable in the future. They've laid the ground work for an immense amount of value creation from an AI standpoint. Nvidia is obvious at this point. There's an argument that companies that do AI and robotics, and maybe spaceflight, are going to be overwhelmingly almost all of the value."

Sawyer Merritt

4,473,089 просмотров • 7 месяцев назад

The AI Cold War: USA🇺🇸 vs China🇨🇳 On E221, the besties discussed how US efforts to impede China’s AI progress by restricting GPU exports are producing unintended consequences. Chamath Palihapitiya: "The US government is really trying to make sure that these next-gen GPUs don't go directly to China, but also don't go to countries that could then redirect them into China." Gavin Baker: " We're putting enough friction into the system that it does theoretically give America an advantage at the cost of creating tremendous incentives for China to develop their own semiconductor ecosystem and ... you know, necessity is the mother of innovation." " These export controls are creating an immense incentive for China to be really algorithmically innovative." "And you saw that with DeepSeek where there were some real algorithmic innovations." @jason: " Said another way, if we squeeze too tightly on letting them buy the Nvidia chips, they might make a better Nvidia." Chamath: "They're trying now." Jason: "What are the chances they succeed in your mind, Gavin?" Gavin: " In the next five years, I think zero. I think it's really, really hard." "But over ten years, who knows?"
0:55

The AI Cold War: USA🇺🇸 vs China🇨🇳 On E221, the besties discussed how US efforts to impede China’s AI progress by restricting GPU exports are producing unintended consequences. Chamath Palihapitiya: "The US government is really trying to make sure that these next-gen GPUs don't go directly to China, but also don't go to countries that could then redirect them into China." Gavin Baker: " We're putting enough friction into the system that it does theoretically give America an advantage at the cost of creating tremendous incentives for China to develop their own semiconductor ecosystem and ... you know, necessity is the mother of innovation." " These export controls are creating an immense incentive for China to be really algorithmically innovative." "And you saw that with DeepSeek where there were some real algorithmic innovations." @jason: " Said another way, if we squeeze too tightly on letting them buy the Nvidia chips, they might make a better Nvidia." Chamath: "They're trying now." Jason: "What are the chances they succeed in your mind, Gavin?" Gavin: " In the next five years, I think zero. I think it's really, really hard." "But over ten years, who knows?"

The All-In Podcast

49,734 просмотров • 1 год назад