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07-14

Since mem makers said they will need years to build new facilities, and years to fully reach output capacity, it logically means it will take years to reach high margins and revenue assuming the AI bubble doesn't crash. If it crashes, today's profits in cash will be their only chance of survival. Spending early on huge expansions is lethal to this line of business.

04-27

$CoreWeave, Inc.(CRWV)$ lol every key person consistently selling off in the company

04-16

finally something actually insightful amidst all the other junk articles

Sorry, the original content has been removed

2025-11-20

wish we had the option to block paywall sources. waste of time and space.

NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ

2024-05-24

can NVIDIA produce enough chips to keep up with demand? How much higher can prices push? If every $1 spent by enterprises can bring $7 ROI, then there is gap to exploit!

Nvidia's Business Is Booming. Here's What Could Slow It Down

2024-05-07

hang in there. Patience.

Go to Tiger App to see more news

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mem makers said they will need years to build new facilities, and years to fully reach output capacity, it logically means it will take years to reach high margins and revenue assuming the AI bubble doesn't crash. 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Spending early on huge expansions is lethal to this line of business.","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/585669804654944","isVote":1,"tweetType":1,"viewCount":301,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":558000231457168,"gmtCreate":1777262315015,"gmtModify":1777262318072,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/CRWV\">$CoreWeave, Inc.(CRWV)$</a> lol every key person consistently selling off in the company","listText":"<a href=\"https://ttm.financial/S/CRWV\">$CoreWeave, Inc.(CRWV)$</a> lol every key person consistently selling off in the company","text":"$CoreWeave, Inc.(CRWV)$ lol every key person consistently selling off in the company","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/558000231457168","isVote":1,"tweetType":1,"viewCount":195,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":554330852982848,"gmtCreate":1776345781049,"gmtModify":1776346324137,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"finally something actually insightful amidst all the other junk articles","listText":"finally something actually insightful amidst all the other junk articles","text":"finally something actually insightful amidst all the other junk articles","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/554330852982848","repostId":"1135864585","repostType":2,"isVote":1,"tweetType":1,"viewCount":219,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":502198247093016,"gmtCreate":1763616632368,"gmtModify":1763617608137,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"wish we had the option to block paywall sources. waste of time and space.","listText":"wish we had the option to block paywall sources. waste of time and space.","text":"wish we had the option to block paywall sources. waste of time and space.","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/502198247093016","repostId":"2584791975","repostType":2,"repost":{"id":"2584791975","kind":"highlight","weMediaInfo":{"introduction":"Stock Market Quotes, Business News, Financial News, Trading Ideas, and Stock Research by Professionals","home_visible":0,"media_name":"Benzinga","id":"1052270027","head_image":"https://static.tigerbbs.com/d08bf7808052c0ca9deb4e944cae32aa"},"pubTimestamp":1763587371,"share":"https://ttm.financial/m/news/2584791975?lang=en_US&edition=fundamental","pubTime":"2025-11-20 05:22","market":"us","language":"en","title":"NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ","url":"https://stock-news.laohu8.com/highlight/detail?id=2584791975","media":"Benzinga","summary":"NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ","content":"<html><body><p>NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ</p></body></html>","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; 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How much higher can prices push? If every $1 spent by enterprises can bring $7 ROI, then there is gap to exploit!","listText":"can NVIDIA produce enough chips to keep up with demand? How much higher can prices push? If every $1 spent by enterprises can bring $7 ROI, then there is gap to exploit!","text":"can NVIDIA produce enough chips to keep up with demand? How much higher can prices push? If every $1 spent by enterprises can bring $7 ROI, then there is gap to exploit!","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":4,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/309074998292600","repostId":"2437420747","repostType":4,"repost":{"id":"2437420747","kind":"highlight","weMediaInfo":{"introduction":"Dow Jones publishes the world’s most trusted business news and financial information in a variety of media.","home_visible":0,"media_name":"Dow Jones","id":"106","head_image":"https://static.tigerbbs.com/150f88aa4d182df19190059f4a365e99"},"pubTimestamp":1716458130,"share":"https://ttm.financial/m/news/2437420747?lang=en_US&edition=fundamental","pubTime":"2024-05-23 17:55","market":"fut","language":"en","title":"Nvidia's Business Is Booming. Here's What Could Slow It Down","url":"https://stock-news.laohu8.com/highlight/detail?id=2437420747","media":"Dow Jones","summary":"Nvidia is riding high after another quarter of blockbuster sales and earnings, even as threats are emerging that could weaken the company's position at the center of the artificial intelligence boom.Rivals and key customers are looking to produce chips that can close the gap with Nvidia's products. Meanwhile, the AI market, which has proven tricky for some startups, is shifting in ways that could diminish the popularity of Nvidia's chips.Despite the power and promise of AI, startups are struggling to come up with a business model that can recoup the massive investment in hardware the technology requires. Sequoia Capital estimated in March that the industry put $50 billion into Nvidia's chips to train large language models, but generative AI startups had only made $3 billion in revenue.Some AI startups that built products using Nvidia's AI chips have run into turmoil, including Inflection AI, a Nvidia-backed company that had its co-founder and other employees decamp for Microsoft in Mar","content":"<html><head></head><body><p>Nvidia is riding high after another quarter of blockbuster sales and earnings, even as threats are emerging that could weaken the company&#39;s position at the center of the artificial intelligence boom.</p><p>Rivals and key customers are looking to produce chips that can close the gap with Nvidia&#39;s products. Meanwhile, the AI market, which has proven tricky for some startups, is shifting in ways that could diminish the popularity of Nvidia&#39;s chips.</p><p>Despite the power and promise of AI, startups are struggling to come up with a business model that can recoup the massive investment in hardware the technology requires. Sequoia Capital estimated in March that the industry put $50 billion into Nvidia&#39;s chips to train large language models, but generative AI startups had only made $3 billion in revenue.</p><p>Some AI startups that built products using Nvidia&#39;s AI chips have run into turmoil, including Inflection AI, a Nvidia-backed company that had its co-founder and other employees decamp for Microsoft in March. The chief executive of Stability AI, which built the popular image-generation AI tool Stable Diffusion, left abruptly in March.</p><p>AI companies big and small also are increasingly looking for ways to build and deploy smaller models that can be effective for specific tasks but don&#39;t require as much of the computational firepower that depends on Nvidia&#39;s chips.</p><p>Depending on how they play out, those factors could help take some of the gusto out of a yearlong bonanza for Nvidia, whose sales tripled in the latest quarter and are projected to double in the second quarter. The success has pushed Nvidia&#39;s stock price to record highs and led the company to more than double its dividend and announce a 10-for-1 stock split.</p><p>In an interview, Chief Executive Jensen Huang laid out ways the company is positioning itself to grow despite challenges. He described an expanding role for Nvidia, moving beyond making chips into crafting the data centers that he sees as modern digital factories that churn out artificial intelligence. In addition to its AI chips, Nvidia makes central processing chips, networking chips and software, among other components that are critical in AI.</p><p>&#34;This is not a chip business,&#34; he said. &#34;You&#39;re building data centers, and if anybody&#39;s ever seen a data center, go take a look and imagine the unbelievable amount of technology that goes into building these things.&#34;</p><p>Louis Miscioscia, an analyst at Daiwa Capital Markets, said in a note that Nvidia was in the right place at the right time, acting as the leading supplier to a boom that could rival the introduction of personal computers, mobile phones and the internet. &#34;AI is big, but could be even bigger than these world-changing events,&#34; he said.</p><p>A big question for investors is whether Nvidia can keep up the momentum or if the market will drop off amid a confluence of market and competitive challenges.</p><p>Nvidia&#39;s chip-making competitors are increasing their game, releasing their own AI chips that they have claimed are better, at least at some AI computing tasks. They are also aiming to displace Nvidia&#39;s dominance in software used to access its GPUs, responding to demand from customers who want alternatives. Nvidia&#39;s market share in AI chips is estimated at above 80%.</p><p>&#34;The current reliance on a single chip manufacturer limits customer choice and can hinder innovation,&#34; said Rodrigo Liang, the chief executive of SambaNova Systems, an AI chip startup that is competing with Nvidia.</p><p>Advanced Micro Devices CEO Lisa Su said last month that her company expected about $4 billion in revenue from AI chips this year. Intel launched a new generation of its AI chips in April, and CEO Pat Gelsinger said in a call with analysts that the company expected $500 million in revenue from those chips in the second half of the year.</p><p>Big tech companies like Amazon, Google, Meta and Microsoft are opening another front against Nvidia by designing their own chips and having them made by contract manufacturers.</p><p>Google, which has been making its own AI chips for years through a partnership with chip maker Broadcom, unveiled a new generation of its AI chips this month. Amazon announced new AI chips in November, the same month Microsoft said it too would start making custom AI chips.</p><p>Industry analysis firm TechInsights estimated this week that Google became the third-largest designer of chips for data centers in 2023, after Nvidia and Intel. Broadcom CEO Hock Tan said in an internal address this year that his company&#39;s custom chip division, which mostly helped Google make AI chips, was bringing in over $1 billion in operating profit a quarter, underlining how much money Google is spending on the effort.</p><p>Microsoft also recently said it would offer cloud-computing customers access to AMD&#39;s AI chips, giving them an alternative to Nvidia.</p><p>Hans Mosesman, an analyst at Rosenblatt Securities, said in a note that Nvidia was expected to lose market share in the percentage of the world&#39;s AI chips that it makes because of the competitive pressure. But he said it was likely to maintain and even increase its overall share of the AI computing landscape because of moves it was making to grow its presence in other areas of computing and in software.</p><p>Beyond the direct challenges in chip-making, Nvidia will have to adapt to a changing AI market to stay ahead. For much of the first year of the AI boom, the focus of investment has been on building, or training, generative AI models, requiring enormous computing ability that is well suited to Nvidia&#39;s chips.</p><p>Those expensive chips are less critical in the deployment phase, known as inference, when models are asked to process new information and respond. Chief Financial Officer Colette Kress said Wednesday that more than 40% of the company&#39;s sales of data center chips in the past year were already for that purpose.</p><p>There are also broader threats to the AI boom, such as the ability to build data centers to house the AI chips and produce enough electricity.</p><p>In addition, companies are focusing on how to build and deploy powerful AI systems more efficiently. Still, as companies look to squeeze more computation out of each Nvidia chip, that doesn&#39;t mean demand will necessarily wane, said Jared Quincy Davis, chief executive of AI startup Foundry Technologies.</p><p>&#34;I think their belief is very much like ours, that when you make things 100 times more efficient, you grow the market by much more than 100 times,&#34; Davis said. &#34;The better the economics of doing things with chips is, the bigger the markets will be.&#34;</p><p>Huang said some regions of the world could produce a limited amount of power, and for them, the important thing was to get the best chips to maximize what they could do. But in some countries, there was excess energy that could be harnessed for AI, he said.</p><p>&#34;It&#39;s not being exported, there&#39;s no available power grids to take it to different places, so it&#39;s a great place to build data centers,&#34; he said. &#34;AI doesn&#39;t care where it&#39;s trained.&#34;</p><p>Nvidia has responded to its growing challenges by pushing ahead with new generations of chips. The company is expecting to release later this year the next versions of its most advanced AI chips, known as Blackwell, with further updates annually.</p><p>The company also is expanding the reach of its business in data centers where AI computation happens. It is offering a growing menu of networking chips and other infrastructure customers need to build big AI computation systems, what Huang often refers to as &#34;AI factories.&#34;</p><p>&#34;We&#39;re producing something that most people at the moment don&#39;t understand. There will be new factories created, and we&#39;re going to produce intelligence at scale,&#34; he said at a conference this month in Santa Clara.</p><p>Huang&#39;s wide-ranging ambition to shape the future of computing should help Nvidia battle competitors looking to encroach on its AI dominance, said Stacy Rasgon, an analyst at Bernstein Research.</p><p>&#34;It&#39;s on them to make sure that they can keep the moat wide, and right now I&#39;d say they are doing a pretty good job,&#34; Rasgon said.</p><p></p></body></html>","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>Nvidia's Business Is Booming. Here's What Could Slow It Down</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; }\nul,ol{ margin-left:2em; }\nul{ list-style:disc; }\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nNvidia's Business Is Booming. Here's What Could Slow It Down\n</h2>\n\n<h4 class=\"meta\">\n\n\n<div class=\"head\" \">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://static.tigerbbs.com/150f88aa4d182df19190059f4a365e99);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">Dow Jones </p>\n<p class=\"h-time\">2024-05-23 17:55</p>\n</div>\n\n</div>\n\n\n</h4>\n\n</header>\n<article>\n<html><head></head><body><p>Nvidia is riding high after another quarter of blockbuster sales and earnings, even as threats are emerging that could weaken the company&#39;s position at the center of the artificial intelligence boom.</p><p>Rivals and key customers are looking to produce chips that can close the gap with Nvidia&#39;s products. Meanwhile, the AI market, which has proven tricky for some startups, is shifting in ways that could diminish the popularity of Nvidia&#39;s chips.</p><p>Despite the power and promise of AI, startups are struggling to come up with a business model that can recoup the massive investment in hardware the technology requires. Sequoia Capital estimated in March that the industry put $50 billion into Nvidia&#39;s chips to train large language models, but generative AI startups had only made $3 billion in revenue.</p><p>Some AI startups that built products using Nvidia&#39;s AI chips have run into turmoil, including Inflection AI, a Nvidia-backed company that had its co-founder and other employees decamp for Microsoft in March. The chief executive of Stability AI, which built the popular image-generation AI tool Stable Diffusion, left abruptly in March.</p><p>AI companies big and small also are increasingly looking for ways to build and deploy smaller models that can be effective for specific tasks but don&#39;t require as much of the computational firepower that depends on Nvidia&#39;s chips.</p><p>Depending on how they play out, those factors could help take some of the gusto out of a yearlong bonanza for Nvidia, whose sales tripled in the latest quarter and are projected to double in the second quarter. The success has pushed Nvidia&#39;s stock price to record highs and led the company to more than double its dividend and announce a 10-for-1 stock split.</p><p>In an interview, Chief Executive Jensen Huang laid out ways the company is positioning itself to grow despite challenges. He described an expanding role for Nvidia, moving beyond making chips into crafting the data centers that he sees as modern digital factories that churn out artificial intelligence. In addition to its AI chips, Nvidia makes central processing chips, networking chips and software, among other components that are critical in AI.</p><p>&#34;This is not a chip business,&#34; he said. &#34;You&#39;re building data centers, and if anybody&#39;s ever seen a data center, go take a look and imagine the unbelievable amount of technology that goes into building these things.&#34;</p><p>Louis Miscioscia, an analyst at Daiwa Capital Markets, said in a note that Nvidia was in the right place at the right time, acting as the leading supplier to a boom that could rival the introduction of personal computers, mobile phones and the internet. &#34;AI is big, but could be even bigger than these world-changing events,&#34; he said.</p><p>A big question for investors is whether Nvidia can keep up the momentum or if the market will drop off amid a confluence of market and competitive challenges.</p><p>Nvidia&#39;s chip-making competitors are increasing their game, releasing their own AI chips that they have claimed are better, at least at some AI computing tasks. They are also aiming to displace Nvidia&#39;s dominance in software used to access its GPUs, responding to demand from customers who want alternatives. Nvidia&#39;s market share in AI chips is estimated at above 80%.</p><p>&#34;The current reliance on a single chip manufacturer limits customer choice and can hinder innovation,&#34; said Rodrigo Liang, the chief executive of SambaNova Systems, an AI chip startup that is competing with Nvidia.</p><p>Advanced Micro Devices CEO Lisa Su said last month that her company expected about $4 billion in revenue from AI chips this year. Intel launched a new generation of its AI chips in April, and CEO Pat Gelsinger said in a call with analysts that the company expected $500 million in revenue from those chips in the second half of the year.</p><p>Big tech companies like Amazon, Google, Meta and Microsoft are opening another front against Nvidia by designing their own chips and having them made by contract manufacturers.</p><p>Google, which has been making its own AI chips for years through a partnership with chip maker Broadcom, unveiled a new generation of its AI chips this month. Amazon announced new AI chips in November, the same month Microsoft said it too would start making custom AI chips.</p><p>Industry analysis firm TechInsights estimated this week that Google became the third-largest designer of chips for data centers in 2023, after Nvidia and Intel. Broadcom CEO Hock Tan said in an internal address this year that his company&#39;s custom chip division, which mostly helped Google make AI chips, was bringing in over $1 billion in operating profit a quarter, underlining how much money Google is spending on the effort.</p><p>Microsoft also recently said it would offer cloud-computing customers access to AMD&#39;s AI chips, giving them an alternative to Nvidia.</p><p>Hans Mosesman, an analyst at Rosenblatt Securities, said in a note that Nvidia was expected to lose market share in the percentage of the world&#39;s AI chips that it makes because of the competitive pressure. But he said it was likely to maintain and even increase its overall share of the AI computing landscape because of moves it was making to grow its presence in other areas of computing and in software.</p><p>Beyond the direct challenges in chip-making, Nvidia will have to adapt to a changing AI market to stay ahead. For much of the first year of the AI boom, the focus of investment has been on building, or training, generative AI models, requiring enormous computing ability that is well suited to Nvidia&#39;s chips.</p><p>Those expensive chips are less critical in the deployment phase, known as inference, when models are asked to process new information and respond. Chief Financial Officer Colette Kress said Wednesday that more than 40% of the company&#39;s sales of data center chips in the past year were already for that purpose.</p><p>There are also broader threats to the AI boom, such as the ability to build data centers to house the AI chips and produce enough electricity.</p><p>In addition, companies are focusing on how to build and deploy powerful AI systems more efficiently. Still, as companies look to squeeze more computation out of each Nvidia chip, that doesn&#39;t mean demand will necessarily wane, said Jared Quincy Davis, chief executive of AI startup Foundry Technologies.</p><p>&#34;I think their belief is very much like ours, that when you make things 100 times more efficient, you grow the market by much more than 100 times,&#34; Davis said. &#34;The better the economics of doing things with chips is, the bigger the markets will be.&#34;</p><p>Huang said some regions of the world could produce a limited amount of power, and for them, the important thing was to get the best chips to maximize what they could do. But in some countries, there was excess energy that could be harnessed for AI, he said.</p><p>&#34;It&#39;s not being exported, there&#39;s no available power grids to take it to different places, so it&#39;s a great place to build data centers,&#34; he said. &#34;AI doesn&#39;t care where it&#39;s trained.&#34;</p><p>Nvidia has responded to its growing challenges by pushing ahead with new generations of chips. The company is expecting to release later this year the next versions of its most advanced AI chips, known as Blackwell, with further updates annually.</p><p>The company also is expanding the reach of its business in data centers where AI computation happens. It is offering a growing menu of networking chips and other infrastructure customers need to build big AI computation systems, what Huang often refers to as &#34;AI factories.&#34;</p><p>&#34;We&#39;re producing something that most people at the moment don&#39;t understand. There will be new factories created, and we&#39;re going to produce intelligence at scale,&#34; he said at a conference this month in Santa Clara.</p><p>Huang&#39;s wide-ranging ambition to shape the future of computing should help Nvidia battle competitors looking to encroach on its AI dominance, said Stacy Rasgon, an analyst at Bernstein Research.</p><p>&#34;It&#39;s on them to make sure that they can keep the moat wide, and right now I&#39;d say they are doing a pretty good job,&#34; Rasgon said.</p><p></p></body></html>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"IE00BBT3K403.USD":"LEGG MASON CLEARBRIDGE TACTICAL DIVIDEND INCOME \"A(USD) ACC","IE00B1BXHZ80.USD":"Legg Mason ClearBridge - US Appreciation A Acc USD","LU0289960550.SGD":"AB FCP I - GLOBAL EQUITY BLEND PORTFOLIO 'A' (SGD) ACC","LU0128525929.USD":"TEMPLETON GLOBAL \"A\" (USD) ACC","LU0130102774.USD":"Natixis Harris Associates US Equity RA USD","BK4534":"瑞士信贷持仓","IE0034235295.USD":"PINEBRIDGE GLOBAL DYNAMIC ASSET ALLOCATION \"A\" (USD) ACC","IE00BFSS8Q28.SGD":"Janus Henderson Balanced A Inc SGD-H","IE0004445239.USD":"JANUS HENDERSON US FORTY \"A2\" (USD) ACC","IE00B19Z9505.USD":"美盛-美国大盘成长股A Acc","GOOGL":"谷歌A","LU0053666078.USD":"摩根大通基金-美国股票A（离岸）美元","BK4533":"AQR资本管理(全球第二大对冲基金)","LU0354030511.USD":"ALLSPRING  U.S. LARGE CAP GROWTH \"I\" (USD) ACC","LU0211327993.USD":"TEMPLETON GLOBAL EQUITY INCOME \"A\" (USD) ACC","LU0354030438.USD":"富国美国大盘成长基金Cl A Acc","BK4553":"喜马拉雅资本持仓","LU0082616367.USD":"摩根大通美国科技A（dist）","GOOG":"谷歌","LU0130103400.USD":"Natixis Harris Associates Global Equity RA USD","BK4535":"淡马锡持仓","MSFT":"微软","IE00BLSP4239.USD":"Legg Mason ClearBridge - Tactical Dividend Income A Mdis USD Plus","LU0348723411.USD":"ALLIANZ GLOBAL HI-TECH GROWTH \"A\" (USD) INC","LU0061474960.USD":"天利环球焦点基金AU Acc","LU1814569148.SGD":"WELLINGTON GLOBAL QUALITY GROWTH \"D\" (SGDHDG) ACC","BK4538":"云计算","BK4549":"软银资本持仓","LU0528227936.USD":"富达环球人口趋势基金A-ACC","LU0494093205.USD":"贝莱德ESG灵活多元资产A2 USD-H","LU0965509283.SGD":"AB LOW VOLATILITY EQUITY PORTFOLIO \"AD\" (SGDHDG) INC","LU1914381329.SGD":"Allianz Best Styles Global Equity Cl ET Acc H2-SGD","IE00B3S45H60.SGD":"Neuberger Berman US Multicap Opportunities A Acc SGD-H","LU0316494557.USD":"FRANKLIN GLOBAL FUNDAMENTAL STRATEGIES \"A\" ACC","BK4548":"巴美列捷福持仓","LU0061475181.USD":"THREADNEEDLE (LUX) AMERICAN \"AU\" (USD) ACC","LU0109391861.USD":"富兰克林美国机遇基金A Acc","IE00BJJMRX11.SGD":"Janus Henderson Balanced A Acc SGD","NVDA":"英伟达","LU0079474960.USD":"联博美国增长基金A","GB00BDT5M118.USD":"天利环球扩展Alpha基金A Acc","IE00BJTD4N35.SGD":"Neuberger Berman US Long Short Equity A1  Acc SGD-H","LU0256863811.USD":"ALLIANZ US EQUITY \"A\" INC","LU0061474705.USD":"THREADNEEDLE (LUX) GLOBAL DYNAMIC REAL RETURN \"AU\" (USD) ACC","IE00B1XK9C88.USD":"PINEBRIDGE US LARGE CAP RESEARCH ENHANCED \"A\" (USD) ACC","IE00B7KXQ091.USD":"Janus Henderson Balanced A Inc USD","BK4532":"文艺复兴科技持仓","BK4554":"元宇宙及AR概念","INTC":"英特尔","LU1280957306.USD":"THREADNEEDLE (LUX) US CONTRARIAN CORE EQUITIES \"AUP\" (USD) INC"},"source_url":"https://dowjonesnews.com/newdjn/logon.aspx?AL=N","is_english":true,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"2437420747","content_text":"Nvidia is riding high after another quarter of blockbuster sales and earnings, even as threats are emerging that could weaken the company's position at the center of the artificial intelligence boom.Rivals and key customers are looking to produce chips that can close the gap with Nvidia's products. Meanwhile, the AI market, which has proven tricky for some startups, is shifting in ways that could diminish the popularity of Nvidia's chips.Despite the power and promise of AI, startups are struggling to come up with a business model that can recoup the massive investment in hardware the technology requires. Sequoia Capital estimated in March that the industry put $50 billion into Nvidia's chips to train large language models, but generative AI startups had only made $3 billion in revenue.Some AI startups that built products using Nvidia's AI chips have run into turmoil, including Inflection AI, a Nvidia-backed company that had its co-founder and other employees decamp for Microsoft in March. The chief executive of Stability AI, which built the popular image-generation AI tool Stable Diffusion, left abruptly in March.AI companies big and small also are increasingly looking for ways to build and deploy smaller models that can be effective for specific tasks but don't require as much of the computational firepower that depends on Nvidia's chips.Depending on how they play out, those factors could help take some of the gusto out of a yearlong bonanza for Nvidia, whose sales tripled in the latest quarter and are projected to double in the second quarter. The success has pushed Nvidia's stock price to record highs and led the company to more than double its dividend and announce a 10-for-1 stock split.In an interview, Chief Executive Jensen Huang laid out ways the company is positioning itself to grow despite challenges. He described an expanding role for Nvidia, moving beyond making chips into crafting the data centers that he sees as modern digital factories that churn out artificial intelligence. In addition to its AI chips, Nvidia makes central processing chips, networking chips and software, among other components that are critical in AI.\"This is not a chip business,\" he said. \"You're building data centers, and if anybody's ever seen a data center, go take a look and imagine the unbelievable amount of technology that goes into building these things.\"Louis Miscioscia, an analyst at Daiwa Capital Markets, said in a note that Nvidia was in the right place at the right time, acting as the leading supplier to a boom that could rival the introduction of personal computers, mobile phones and the internet. \"AI is big, but could be even bigger than these world-changing events,\" he said.A big question for investors is whether Nvidia can keep up the momentum or if the market will drop off amid a confluence of market and competitive challenges.Nvidia's chip-making competitors are increasing their game, releasing their own AI chips that they have claimed are better, at least at some AI computing tasks. They are also aiming to displace Nvidia's dominance in software used to access its GPUs, responding to demand from customers who want alternatives. Nvidia's market share in AI chips is estimated at above 80%.\"The current reliance on a single chip manufacturer limits customer choice and can hinder innovation,\" said Rodrigo Liang, the chief executive of SambaNova Systems, an AI chip startup that is competing with Nvidia.Advanced Micro Devices CEO Lisa Su said last month that her company expected about $4 billion in revenue from AI chips this year. Intel launched a new generation of its AI chips in April, and CEO Pat Gelsinger said in a call with analysts that the company expected $500 million in revenue from those chips in the second half of the year.Big tech companies like Amazon, Google, Meta and Microsoft are opening another front against Nvidia by designing their own chips and having them made by contract manufacturers.Google, which has been making its own AI chips for years through a partnership with chip maker Broadcom, unveiled a new generation of its AI chips this month. Amazon announced new AI chips in November, the same month Microsoft said it too would start making custom AI chips.Industry analysis firm TechInsights estimated this week that Google became the third-largest designer of chips for data centers in 2023, after Nvidia and Intel. Broadcom CEO Hock Tan said in an internal address this year that his company's custom chip division, which mostly helped Google make AI chips, was bringing in over $1 billion in operating profit a quarter, underlining how much money Google is spending on the effort.Microsoft also recently said it would offer cloud-computing customers access to AMD's AI chips, giving them an alternative to Nvidia.Hans Mosesman, an analyst at Rosenblatt Securities, said in a note that Nvidia was expected to lose market share in the percentage of the world's AI chips that it makes because of the competitive pressure. But he said it was likely to maintain and even increase its overall share of the AI computing landscape because of moves it was making to grow its presence in other areas of computing and in software.Beyond the direct challenges in chip-making, Nvidia will have to adapt to a changing AI market to stay ahead. For much of the first year of the AI boom, the focus of investment has been on building, or training, generative AI models, requiring enormous computing ability that is well suited to Nvidia's chips.Those expensive chips are less critical in the deployment phase, known as inference, when models are asked to process new information and respond. Chief Financial Officer Colette Kress said Wednesday that more than 40% of the company's sales of data center chips in the past year were already for that purpose.There are also broader threats to the AI boom, such as the ability to build data centers to house the AI chips and produce enough electricity.In addition, companies are focusing on how to build and deploy powerful AI systems more efficiently. Still, as companies look to squeeze more computation out of each Nvidia chip, that doesn't mean demand will necessarily wane, said Jared Quincy Davis, chief executive of AI startup Foundry Technologies.\"I think their belief is very much like ours, that when you make things 100 times more efficient, you grow the market by much more than 100 times,\" Davis said. \"The better the economics of doing things with chips is, the bigger the markets will be.\"Huang said some regions of the world could produce a limited amount of power, and for them, the important thing was to get the best chips to maximize what they could do. But in some countries, there was excess energy that could be harnessed for AI, he said.\"It's not being exported, there's no available power grids to take it to different places, so it's a great place to build data centers,\" he said. \"AI doesn't care where it's trained.\"Nvidia has responded to its growing challenges by pushing ahead with new generations of chips. The company is expecting to release later this year the next versions of its most advanced AI chips, known as Blackwell, with further updates annually.The company also is expanding the reach of its business in data centers where AI computation happens. It is offering a growing menu of networking chips and other infrastructure customers need to build big AI computation systems, what Huang often refers to as \"AI factories.\"\"We're producing something that most people at the moment don't understand. There will be new factories created, and we're going to produce intelligence at scale,\" he said at a conference this month in Santa Clara.Huang's wide-ranging ambition to shape the future of computing should help Nvidia battle competitors looking to encroach on its AI dominance, said Stacy Rasgon, an analyst at Bernstein Research.\"It's on them to make sure that they can keep the moat wide, and right now I'd say they are doing a pretty good job,\" Rasgon said.","news_type":1,"symbols_score_info":{"GOOG":1.1,"MSFT":1.1,"NVDA":0.9,"GOOGL":1.1,"INTC":1.1}},"isVote":1,"tweetType":1,"viewCount":357,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":303219187245272,"gmtCreate":1715063731405,"gmtModify":1715064047850,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"hang in there. Patience.","listText":"hang in there. Patience.","text":"hang in there. Patience.","images":[{"img":"https://community-static.tradeup.com/news/cc622ff2b38030bf9fb791d5bc914b07","width":"1125","height":"1476"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/303219187245272","isVote":1,"tweetType":1,"viewCount":263,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0}],"hots":[{"id":309074998292600,"gmtCreate":1716485561146,"gmtModify":1716489131464,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"can NVIDIA produce enough chips to keep up with demand? How much higher can prices push? If every $1 spent by enterprises can bring $7 ROI, then there is gap to exploit!","listText":"can NVIDIA produce enough chips to keep up with demand? How much higher can prices push? If every $1 spent by enterprises can bring $7 ROI, then there is gap to exploit!","text":"can NVIDIA produce enough chips to keep up with demand? How much higher can prices push? If every $1 spent by enterprises can bring $7 ROI, then there is gap to exploit!","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":4,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/309074998292600","repostId":"2437420747","repostType":4,"repost":{"id":"2437420747","kind":"highlight","weMediaInfo":{"introduction":"Dow Jones publishes the world’s most trusted business news and financial information in a variety of media.","home_visible":0,"media_name":"Dow Jones","id":"106","head_image":"https://static.tigerbbs.com/150f88aa4d182df19190059f4a365e99"},"pubTimestamp":1716458130,"share":"https://ttm.financial/m/news/2437420747?lang=en_US&edition=fundamental","pubTime":"2024-05-23 17:55","market":"fut","language":"en","title":"Nvidia's Business Is Booming. Here's What Could Slow It Down","url":"https://stock-news.laohu8.com/highlight/detail?id=2437420747","media":"Dow Jones","summary":"Nvidia is riding high after another quarter of blockbuster sales and earnings, even as threats are emerging that could weaken the company's position at the center of the artificial intelligence boom.Rivals and key customers are looking to produce chips that can close the gap with Nvidia's products. Meanwhile, the AI market, which has proven tricky for some startups, is shifting in ways that could diminish the popularity of Nvidia's chips.Despite the power and promise of AI, startups are struggling to come up with a business model that can recoup the massive investment in hardware the technology requires. Sequoia Capital estimated in March that the industry put $50 billion into Nvidia's chips to train large language models, but generative AI startups had only made $3 billion in revenue.Some AI startups that built products using Nvidia's AI chips have run into turmoil, including Inflection AI, a Nvidia-backed company that had its co-founder and other employees decamp for Microsoft in Mar","content":"<html><head></head><body><p>Nvidia is riding high after another quarter of blockbuster sales and earnings, even as threats are emerging that could weaken the company&#39;s position at the center of the artificial intelligence boom.</p><p>Rivals and key customers are looking to produce chips that can close the gap with Nvidia&#39;s products. Meanwhile, the AI market, which has proven tricky for some startups, is shifting in ways that could diminish the popularity of Nvidia&#39;s chips.</p><p>Despite the power and promise of AI, startups are struggling to come up with a business model that can recoup the massive investment in hardware the technology requires. Sequoia Capital estimated in March that the industry put $50 billion into Nvidia&#39;s chips to train large language models, but generative AI startups had only made $3 billion in revenue.</p><p>Some AI startups that built products using Nvidia&#39;s AI chips have run into turmoil, including Inflection AI, a Nvidia-backed company that had its co-founder and other employees decamp for Microsoft in March. The chief executive of Stability AI, which built the popular image-generation AI tool Stable Diffusion, left abruptly in March.</p><p>AI companies big and small also are increasingly looking for ways to build and deploy smaller models that can be effective for specific tasks but don&#39;t require as much of the computational firepower that depends on Nvidia&#39;s chips.</p><p>Depending on how they play out, those factors could help take some of the gusto out of a yearlong bonanza for Nvidia, whose sales tripled in the latest quarter and are projected to double in the second quarter. The success has pushed Nvidia&#39;s stock price to record highs and led the company to more than double its dividend and announce a 10-for-1 stock split.</p><p>In an interview, Chief Executive Jensen Huang laid out ways the company is positioning itself to grow despite challenges. He described an expanding role for Nvidia, moving beyond making chips into crafting the data centers that he sees as modern digital factories that churn out artificial intelligence. In addition to its AI chips, Nvidia makes central processing chips, networking chips and software, among other components that are critical in AI.</p><p>&#34;This is not a chip business,&#34; he said. &#34;You&#39;re building data centers, and if anybody&#39;s ever seen a data center, go take a look and imagine the unbelievable amount of technology that goes into building these things.&#34;</p><p>Louis Miscioscia, an analyst at Daiwa Capital Markets, said in a note that Nvidia was in the right place at the right time, acting as the leading supplier to a boom that could rival the introduction of personal computers, mobile phones and the internet. &#34;AI is big, but could be even bigger than these world-changing events,&#34; he said.</p><p>A big question for investors is whether Nvidia can keep up the momentum or if the market will drop off amid a confluence of market and competitive challenges.</p><p>Nvidia&#39;s chip-making competitors are increasing their game, releasing their own AI chips that they have claimed are better, at least at some AI computing tasks. They are also aiming to displace Nvidia&#39;s dominance in software used to access its GPUs, responding to demand from customers who want alternatives. Nvidia&#39;s market share in AI chips is estimated at above 80%.</p><p>&#34;The current reliance on a single chip manufacturer limits customer choice and can hinder innovation,&#34; said Rodrigo Liang, the chief executive of SambaNova Systems, an AI chip startup that is competing with Nvidia.</p><p>Advanced Micro Devices CEO Lisa Su said last month that her company expected about $4 billion in revenue from AI chips this year. Intel launched a new generation of its AI chips in April, and CEO Pat Gelsinger said in a call with analysts that the company expected $500 million in revenue from those chips in the second half of the year.</p><p>Big tech companies like Amazon, Google, Meta and Microsoft are opening another front against Nvidia by designing their own chips and having them made by contract manufacturers.</p><p>Google, which has been making its own AI chips for years through a partnership with chip maker Broadcom, unveiled a new generation of its AI chips this month. Amazon announced new AI chips in November, the same month Microsoft said it too would start making custom AI chips.</p><p>Industry analysis firm TechInsights estimated this week that Google became the third-largest designer of chips for data centers in 2023, after Nvidia and Intel. Broadcom CEO Hock Tan said in an internal address this year that his company&#39;s custom chip division, which mostly helped Google make AI chips, was bringing in over $1 billion in operating profit a quarter, underlining how much money Google is spending on the effort.</p><p>Microsoft also recently said it would offer cloud-computing customers access to AMD&#39;s AI chips, giving them an alternative to Nvidia.</p><p>Hans Mosesman, an analyst at Rosenblatt Securities, said in a note that Nvidia was expected to lose market share in the percentage of the world&#39;s AI chips that it makes because of the competitive pressure. But he said it was likely to maintain and even increase its overall share of the AI computing landscape because of moves it was making to grow its presence in other areas of computing and in software.</p><p>Beyond the direct challenges in chip-making, Nvidia will have to adapt to a changing AI market to stay ahead. For much of the first year of the AI boom, the focus of investment has been on building, or training, generative AI models, requiring enormous computing ability that is well suited to Nvidia&#39;s chips.</p><p>Those expensive chips are less critical in the deployment phase, known as inference, when models are asked to process new information and respond. Chief Financial Officer Colette Kress said Wednesday that more than 40% of the company&#39;s sales of data center chips in the past year were already for that purpose.</p><p>There are also broader threats to the AI boom, such as the ability to build data centers to house the AI chips and produce enough electricity.</p><p>In addition, companies are focusing on how to build and deploy powerful AI systems more efficiently. Still, as companies look to squeeze more computation out of each Nvidia chip, that doesn&#39;t mean demand will necessarily wane, said Jared Quincy Davis, chief executive of AI startup Foundry Technologies.</p><p>&#34;I think their belief is very much like ours, that when you make things 100 times more efficient, you grow the market by much more than 100 times,&#34; Davis said. &#34;The better the economics of doing things with chips is, the bigger the markets will be.&#34;</p><p>Huang said some regions of the world could produce a limited amount of power, and for them, the important thing was to get the best chips to maximize what they could do. But in some countries, there was excess energy that could be harnessed for AI, he said.</p><p>&#34;It&#39;s not being exported, there&#39;s no available power grids to take it to different places, so it&#39;s a great place to build data centers,&#34; he said. &#34;AI doesn&#39;t care where it&#39;s trained.&#34;</p><p>Nvidia has responded to its growing challenges by pushing ahead with new generations of chips. The company is expecting to release later this year the next versions of its most advanced AI chips, known as Blackwell, with further updates annually.</p><p>The company also is expanding the reach of its business in data centers where AI computation happens. It is offering a growing menu of networking chips and other infrastructure customers need to build big AI computation systems, what Huang often refers to as &#34;AI factories.&#34;</p><p>&#34;We&#39;re producing something that most people at the moment don&#39;t understand. There will be new factories created, and we&#39;re going to produce intelligence at scale,&#34; he said at a conference this month in Santa Clara.</p><p>Huang&#39;s wide-ranging ambition to shape the future of computing should help Nvidia battle competitors looking to encroach on its AI dominance, said Stacy Rasgon, an analyst at Bernstein Research.</p><p>&#34;It&#39;s on them to make sure that they can keep the moat wide, and right now I&#39;d say they are doing a pretty good job,&#34; Rasgon said.</p><p></p></body></html>","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>Nvidia's Business Is Booming. Here's What Could Slow It Down</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; }\nul,ol{ margin-left:2em; }\nul{ list-style:disc; }\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nNvidia's Business Is Booming. Here's What Could Slow It Down\n</h2>\n\n<h4 class=\"meta\">\n\n\n<div class=\"head\" \">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://static.tigerbbs.com/150f88aa4d182df19190059f4a365e99);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">Dow Jones </p>\n<p class=\"h-time\">2024-05-23 17:55</p>\n</div>\n\n</div>\n\n\n</h4>\n\n</header>\n<article>\n<html><head></head><body><p>Nvidia is riding high after another quarter of blockbuster sales and earnings, even as threats are emerging that could weaken the company&#39;s position at the center of the artificial intelligence boom.</p><p>Rivals and key customers are looking to produce chips that can close the gap with Nvidia&#39;s products. Meanwhile, the AI market, which has proven tricky for some startups, is shifting in ways that could diminish the popularity of Nvidia&#39;s chips.</p><p>Despite the power and promise of AI, startups are struggling to come up with a business model that can recoup the massive investment in hardware the technology requires. Sequoia Capital estimated in March that the industry put $50 billion into Nvidia&#39;s chips to train large language models, but generative AI startups had only made $3 billion in revenue.</p><p>Some AI startups that built products using Nvidia&#39;s AI chips have run into turmoil, including Inflection AI, a Nvidia-backed company that had its co-founder and other employees decamp for Microsoft in March. The chief executive of Stability AI, which built the popular image-generation AI tool Stable Diffusion, left abruptly in March.</p><p>AI companies big and small also are increasingly looking for ways to build and deploy smaller models that can be effective for specific tasks but don&#39;t require as much of the computational firepower that depends on Nvidia&#39;s chips.</p><p>Depending on how they play out, those factors could help take some of the gusto out of a yearlong bonanza for Nvidia, whose sales tripled in the latest quarter and are projected to double in the second quarter. The success has pushed Nvidia&#39;s stock price to record highs and led the company to more than double its dividend and announce a 10-for-1 stock split.</p><p>In an interview, Chief Executive Jensen Huang laid out ways the company is positioning itself to grow despite challenges. He described an expanding role for Nvidia, moving beyond making chips into crafting the data centers that he sees as modern digital factories that churn out artificial intelligence. In addition to its AI chips, Nvidia makes central processing chips, networking chips and software, among other components that are critical in AI.</p><p>&#34;This is not a chip business,&#34; he said. &#34;You&#39;re building data centers, and if anybody&#39;s ever seen a data center, go take a look and imagine the unbelievable amount of technology that goes into building these things.&#34;</p><p>Louis Miscioscia, an analyst at Daiwa Capital Markets, said in a note that Nvidia was in the right place at the right time, acting as the leading supplier to a boom that could rival the introduction of personal computers, mobile phones and the internet. &#34;AI is big, but could be even bigger than these world-changing events,&#34; he said.</p><p>A big question for investors is whether Nvidia can keep up the momentum or if the market will drop off amid a confluence of market and competitive challenges.</p><p>Nvidia&#39;s chip-making competitors are increasing their game, releasing their own AI chips that they have claimed are better, at least at some AI computing tasks. They are also aiming to displace Nvidia&#39;s dominance in software used to access its GPUs, responding to demand from customers who want alternatives. Nvidia&#39;s market share in AI chips is estimated at above 80%.</p><p>&#34;The current reliance on a single chip manufacturer limits customer choice and can hinder innovation,&#34; said Rodrigo Liang, the chief executive of SambaNova Systems, an AI chip startup that is competing with Nvidia.</p><p>Advanced Micro Devices CEO Lisa Su said last month that her company expected about $4 billion in revenue from AI chips this year. Intel launched a new generation of its AI chips in April, and CEO Pat Gelsinger said in a call with analysts that the company expected $500 million in revenue from those chips in the second half of the year.</p><p>Big tech companies like Amazon, Google, Meta and Microsoft are opening another front against Nvidia by designing their own chips and having them made by contract manufacturers.</p><p>Google, which has been making its own AI chips for years through a partnership with chip maker Broadcom, unveiled a new generation of its AI chips this month. Amazon announced new AI chips in November, the same month Microsoft said it too would start making custom AI chips.</p><p>Industry analysis firm TechInsights estimated this week that Google became the third-largest designer of chips for data centers in 2023, after Nvidia and Intel. Broadcom CEO Hock Tan said in an internal address this year that his company&#39;s custom chip division, which mostly helped Google make AI chips, was bringing in over $1 billion in operating profit a quarter, underlining how much money Google is spending on the effort.</p><p>Microsoft also recently said it would offer cloud-computing customers access to AMD&#39;s AI chips, giving them an alternative to Nvidia.</p><p>Hans Mosesman, an analyst at Rosenblatt Securities, said in a note that Nvidia was expected to lose market share in the percentage of the world&#39;s AI chips that it makes because of the competitive pressure. But he said it was likely to maintain and even increase its overall share of the AI computing landscape because of moves it was making to grow its presence in other areas of computing and in software.</p><p>Beyond the direct challenges in chip-making, Nvidia will have to adapt to a changing AI market to stay ahead. For much of the first year of the AI boom, the focus of investment has been on building, or training, generative AI models, requiring enormous computing ability that is well suited to Nvidia&#39;s chips.</p><p>Those expensive chips are less critical in the deployment phase, known as inference, when models are asked to process new information and respond. Chief Financial Officer Colette Kress said Wednesday that more than 40% of the company&#39;s sales of data center chips in the past year were already for that purpose.</p><p>There are also broader threats to the AI boom, such as the ability to build data centers to house the AI chips and produce enough electricity.</p><p>In addition, companies are focusing on how to build and deploy powerful AI systems more efficiently. Still, as companies look to squeeze more computation out of each Nvidia chip, that doesn&#39;t mean demand will necessarily wane, said Jared Quincy Davis, chief executive of AI startup Foundry Technologies.</p><p>&#34;I think their belief is very much like ours, that when you make things 100 times more efficient, you grow the market by much more than 100 times,&#34; Davis said. &#34;The better the economics of doing things with chips is, the bigger the markets will be.&#34;</p><p>Huang said some regions of the world could produce a limited amount of power, and for them, the important thing was to get the best chips to maximize what they could do. But in some countries, there was excess energy that could be harnessed for AI, he said.</p><p>&#34;It&#39;s not being exported, there&#39;s no available power grids to take it to different places, so it&#39;s a great place to build data centers,&#34; he said. &#34;AI doesn&#39;t care where it&#39;s trained.&#34;</p><p>Nvidia has responded to its growing challenges by pushing ahead with new generations of chips. The company is expecting to release later this year the next versions of its most advanced AI chips, known as Blackwell, with further updates annually.</p><p>The company also is expanding the reach of its business in data centers where AI computation happens. It is offering a growing menu of networking chips and other infrastructure customers need to build big AI computation systems, what Huang often refers to as &#34;AI factories.&#34;</p><p>&#34;We&#39;re producing something that most people at the moment don&#39;t understand. There will be new factories created, and we&#39;re going to produce intelligence at scale,&#34; he said at a conference this month in Santa Clara.</p><p>Huang&#39;s wide-ranging ambition to shape the future of computing should help Nvidia battle competitors looking to encroach on its AI dominance, said Stacy Rasgon, an analyst at Bernstein Research.</p><p>&#34;It&#39;s on them to make sure that they can keep the moat wide, and right now I&#39;d say they are doing a pretty good job,&#34; Rasgon said.</p><p></p></body></html>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"IE00BBT3K403.USD":"LEGG MASON CLEARBRIDGE TACTICAL DIVIDEND INCOME \"A(USD) ACC","IE00B1BXHZ80.USD":"Legg Mason ClearBridge - US Appreciation A Acc USD","LU0289960550.SGD":"AB FCP I - GLOBAL EQUITY BLEND PORTFOLIO 'A' (SGD) ACC","LU0128525929.USD":"TEMPLETON GLOBAL \"A\" (USD) ACC","LU0130102774.USD":"Natixis Harris Associates US Equity RA USD","BK4534":"瑞士信贷持仓","IE0034235295.USD":"PINEBRIDGE GLOBAL DYNAMIC ASSET ALLOCATION \"A\" (USD) ACC","IE00BFSS8Q28.SGD":"Janus Henderson Balanced A Inc SGD-H","IE0004445239.USD":"JANUS HENDERSON US FORTY \"A2\" (USD) ACC","IE00B19Z9505.USD":"美盛-美国大盘成长股A Acc","GOOGL":"谷歌A","LU0053666078.USD":"摩根大通基金-美国股票A（离岸）美元","BK4533":"AQR资本管理(全球第二大对冲基金)","LU0354030511.USD":"ALLSPRING  U.S. LARGE CAP GROWTH \"I\" (USD) ACC","LU0211327993.USD":"TEMPLETON GLOBAL EQUITY INCOME \"A\" (USD) ACC","LU0354030438.USD":"富国美国大盘成长基金Cl A Acc","BK4553":"喜马拉雅资本持仓","LU0082616367.USD":"摩根大通美国科技A（dist）","GOOG":"谷歌","LU0130103400.USD":"Natixis Harris Associates Global Equity RA USD","BK4535":"淡马锡持仓","MSFT":"微软","IE00BLSP4239.USD":"Legg Mason ClearBridge - Tactical Dividend Income A Mdis USD Plus","LU0348723411.USD":"ALLIANZ GLOBAL HI-TECH GROWTH \"A\" (USD) INC","LU0061474960.USD":"天利环球焦点基金AU Acc","LU1814569148.SGD":"WELLINGTON GLOBAL QUALITY GROWTH \"D\" (SGDHDG) ACC","BK4538":"云计算","BK4549":"软银资本持仓","LU0528227936.USD":"富达环球人口趋势基金A-ACC","LU0494093205.USD":"贝莱德ESG灵活多元资产A2 USD-H","LU0965509283.SGD":"AB LOW VOLATILITY EQUITY PORTFOLIO \"AD\" (SGDHDG) INC","LU1914381329.SGD":"Allianz Best Styles Global Equity Cl ET Acc H2-SGD","IE00B3S45H60.SGD":"Neuberger Berman US Multicap Opportunities A Acc SGD-H","LU0316494557.USD":"FRANKLIN GLOBAL FUNDAMENTAL STRATEGIES \"A\" ACC","BK4548":"巴美列捷福持仓","LU0061475181.USD":"THREADNEEDLE (LUX) AMERICAN \"AU\" (USD) ACC","LU0109391861.USD":"富兰克林美国机遇基金A Acc","IE00BJJMRX11.SGD":"Janus Henderson Balanced A Acc SGD","NVDA":"英伟达","LU0079474960.USD":"联博美国增长基金A","GB00BDT5M118.USD":"天利环球扩展Alpha基金A Acc","IE00BJTD4N35.SGD":"Neuberger Berman US Long Short Equity A1  Acc SGD-H","LU0256863811.USD":"ALLIANZ US EQUITY \"A\" INC","LU0061474705.USD":"THREADNEEDLE (LUX) GLOBAL DYNAMIC REAL RETURN \"AU\" (USD) ACC","IE00B1XK9C88.USD":"PINEBRIDGE US LARGE CAP RESEARCH ENHANCED \"A\" (USD) ACC","IE00B7KXQ091.USD":"Janus Henderson Balanced A Inc USD","BK4532":"文艺复兴科技持仓","BK4554":"元宇宙及AR概念","INTC":"英特尔","LU1280957306.USD":"THREADNEEDLE (LUX) US CONTRARIAN CORE EQUITIES \"AUP\" (USD) INC"},"source_url":"https://dowjonesnews.com/newdjn/logon.aspx?AL=N","is_english":true,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"2437420747","content_text":"Nvidia is riding high after another quarter of blockbuster sales and earnings, even as threats are emerging that could weaken the company's position at the center of the artificial intelligence boom.Rivals and key customers are looking to produce chips that can close the gap with Nvidia's products. Meanwhile, the AI market, which has proven tricky for some startups, is shifting in ways that could diminish the popularity of Nvidia's chips.Despite the power and promise of AI, startups are struggling to come up with a business model that can recoup the massive investment in hardware the technology requires. Sequoia Capital estimated in March that the industry put $50 billion into Nvidia's chips to train large language models, but generative AI startups had only made $3 billion in revenue.Some AI startups that built products using Nvidia's AI chips have run into turmoil, including Inflection AI, a Nvidia-backed company that had its co-founder and other employees decamp for Microsoft in March. The chief executive of Stability AI, which built the popular image-generation AI tool Stable Diffusion, left abruptly in March.AI companies big and small also are increasingly looking for ways to build and deploy smaller models that can be effective for specific tasks but don't require as much of the computational firepower that depends on Nvidia's chips.Depending on how they play out, those factors could help take some of the gusto out of a yearlong bonanza for Nvidia, whose sales tripled in the latest quarter and are projected to double in the second quarter. The success has pushed Nvidia's stock price to record highs and led the company to more than double its dividend and announce a 10-for-1 stock split.In an interview, Chief Executive Jensen Huang laid out ways the company is positioning itself to grow despite challenges. He described an expanding role for Nvidia, moving beyond making chips into crafting the data centers that he sees as modern digital factories that churn out artificial intelligence. In addition to its AI chips, Nvidia makes central processing chips, networking chips and software, among other components that are critical in AI.\"This is not a chip business,\" he said. \"You're building data centers, and if anybody's ever seen a data center, go take a look and imagine the unbelievable amount of technology that goes into building these things.\"Louis Miscioscia, an analyst at Daiwa Capital Markets, said in a note that Nvidia was in the right place at the right time, acting as the leading supplier to a boom that could rival the introduction of personal computers, mobile phones and the internet. \"AI is big, but could be even bigger than these world-changing events,\" he said.A big question for investors is whether Nvidia can keep up the momentum or if the market will drop off amid a confluence of market and competitive challenges.Nvidia's chip-making competitors are increasing their game, releasing their own AI chips that they have claimed are better, at least at some AI computing tasks. They are also aiming to displace Nvidia's dominance in software used to access its GPUs, responding to demand from customers who want alternatives. Nvidia's market share in AI chips is estimated at above 80%.\"The current reliance on a single chip manufacturer limits customer choice and can hinder innovation,\" said Rodrigo Liang, the chief executive of SambaNova Systems, an AI chip startup that is competing with Nvidia.Advanced Micro Devices CEO Lisa Su said last month that her company expected about $4 billion in revenue from AI chips this year. Intel launched a new generation of its AI chips in April, and CEO Pat Gelsinger said in a call with analysts that the company expected $500 million in revenue from those chips in the second half of the year.Big tech companies like Amazon, Google, Meta and Microsoft are opening another front against Nvidia by designing their own chips and having them made by contract manufacturers.Google, which has been making its own AI chips for years through a partnership with chip maker Broadcom, unveiled a new generation of its AI chips this month. Amazon announced new AI chips in November, the same month Microsoft said it too would start making custom AI chips.Industry analysis firm TechInsights estimated this week that Google became the third-largest designer of chips for data centers in 2023, after Nvidia and Intel. Broadcom CEO Hock Tan said in an internal address this year that his company's custom chip division, which mostly helped Google make AI chips, was bringing in over $1 billion in operating profit a quarter, underlining how much money Google is spending on the effort.Microsoft also recently said it would offer cloud-computing customers access to AMD's AI chips, giving them an alternative to Nvidia.Hans Mosesman, an analyst at Rosenblatt Securities, said in a note that Nvidia was expected to lose market share in the percentage of the world's AI chips that it makes because of the competitive pressure. But he said it was likely to maintain and even increase its overall share of the AI computing landscape because of moves it was making to grow its presence in other areas of computing and in software.Beyond the direct challenges in chip-making, Nvidia will have to adapt to a changing AI market to stay ahead. For much of the first year of the AI boom, the focus of investment has been on building, or training, generative AI models, requiring enormous computing ability that is well suited to Nvidia's chips.Those expensive chips are less critical in the deployment phase, known as inference, when models are asked to process new information and respond. Chief Financial Officer Colette Kress said Wednesday that more than 40% of the company's sales of data center chips in the past year were already for that purpose.There are also broader threats to the AI boom, such as the ability to build data centers to house the AI chips and produce enough electricity.In addition, companies are focusing on how to build and deploy powerful AI systems more efficiently. Still, as companies look to squeeze more computation out of each Nvidia chip, that doesn't mean demand will necessarily wane, said Jared Quincy Davis, chief executive of AI startup Foundry Technologies.\"I think their belief is very much like ours, that when you make things 100 times more efficient, you grow the market by much more than 100 times,\" Davis said. \"The better the economics of doing things with chips is, the bigger the markets will be.\"Huang said some regions of the world could produce a limited amount of power, and for them, the important thing was to get the best chips to maximize what they could do. But in some countries, there was excess energy that could be harnessed for AI, he said.\"It's not being exported, there's no available power grids to take it to different places, so it's a great place to build data centers,\" he said. \"AI doesn't care where it's trained.\"Nvidia has responded to its growing challenges by pushing ahead with new generations of chips. The company is expecting to release later this year the next versions of its most advanced AI chips, known as Blackwell, with further updates annually.The company also is expanding the reach of its business in data centers where AI computation happens. It is offering a growing menu of networking chips and other infrastructure customers need to build big AI computation systems, what Huang often refers to as \"AI factories.\"\"We're producing something that most people at the moment don't understand. There will be new factories created, and we're going to produce intelligence at scale,\" he said at a conference this month in Santa Clara.Huang's wide-ranging ambition to shape the future of computing should help Nvidia battle competitors looking to encroach on its AI dominance, said Stacy Rasgon, an analyst at Bernstein Research.\"It's on them to make sure that they can keep the moat wide, and right now I'd say they are doing a pretty good job,\" Rasgon said.","news_type":1,"symbols_score_info":{"GOOG":1.1,"MSFT":1.1,"NVDA":0.9,"GOOGL":1.1,"INTC":1.1}},"isVote":1,"tweetType":1,"viewCount":357,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":585669804654944,"gmtCreate":1784015977541,"gmtModify":1784015980901,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"Since mem makers said they will need years to build new facilities, and years to fully reach output capacity, it logically means it will take years to reach high margins and revenue assuming the AI bubble doesn't crash. If it crashes, today's profits in cash will be their only chance of survival. Spending early on huge expansions is lethal to this line of business.","listText":"Since mem makers said they will need years to build new facilities, and years to fully reach output capacity, it logically means it will take years to reach high margins and revenue assuming the AI bubble doesn't crash. If it crashes, today's profits in cash will be their only chance of survival. Spending early on huge expansions is lethal to this line of business.","text":"Since mem makers said they will need years to build new facilities, and years to fully reach output capacity, it logically means it will take years to reach high margins and revenue assuming the AI bubble doesn't crash. If it crashes, today's profits in cash will be their only chance of survival. Spending early on huge expansions is lethal to this line of business.","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/585669804654944","isVote":1,"tweetType":1,"viewCount":301,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":558000231457168,"gmtCreate":1777262315015,"gmtModify":1777262318072,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"<a href=\"https://ttm.financial/S/CRWV\">$CoreWeave, Inc.(CRWV)$</a> lol every key person consistently selling off in the company","listText":"<a href=\"https://ttm.financial/S/CRWV\">$CoreWeave, Inc.(CRWV)$</a> lol every key person consistently selling off in the company","text":"$CoreWeave, Inc.(CRWV)$ lol every key person consistently selling off in the company","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/558000231457168","isVote":1,"tweetType":1,"viewCount":195,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":554330852982848,"gmtCreate":1776345781049,"gmtModify":1776346324137,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"finally something actually insightful amidst all the other junk articles","listText":"finally something actually insightful amidst all the other junk articles","text":"finally something actually insightful amidst all the other junk articles","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/554330852982848","repostId":"1135864585","repostType":2,"repost":{"id":"1135864585","kind":"news","weMediaInfo":{"introduction":"Global Stock Market Deep Analysis","home_visible":1,"media_name":"Deep News","id":"1039043262","head_image":"https://community-static.tradeup.com/news/8296859682db4b478146245e72de1922"},"pubTimestamp":1776322587,"share":"https://ttm.financial/m/news/1135864585?lang=en_US&edition=fundamental","pubTime":"2026-04-16 14:56","market":"fut","language":"en","title":"Comparative Analysis of Emerging AI Cloud Providers: CoreWeave and Nebius","url":"https://stock-news.laohu8.com/highlight/detail?id=1135864585","media":"Deep News","summary":"A recent in-depth report provides a systematic comparison of the strategic differences and similarities between two prominent Neocloud companies, CoreWeave, Inc. and NEBIUS. According to the...","content":"<p>A recent in-depth report provides a systematic comparison of the strategic differences and similarities between two prominent Neocloud companies, CoreWeave, Inc. and NEBIUS. According to the analysis, CoreWeave, Inc. has established a leadership position in the industry due to its larger scale, proven execution track record, and highly visible financing pathway. In contrast, NEBIUS is building differentiated optionality value through greater spot market flexibility, a diversified strategy targeting enterprise customers, and a more flexible capital structure.</p>\n<p>The disparity in financial performance is stark. In 2025, CoreWeave, Inc. reported revenue of $51.3 billion, representing a 168% year-over-year increase, with EBITDA reaching $31 billion and a margin of 60%. NEBIUS reported revenue of only $5.3 billion, a 479% year-over-year increase, but posted an EBITDA loss of $65 million, resulting in a negative margin of -12%. However, the growth rates for both companies are impressive. CoreWeave, Inc.'s revenue is projected to grow to approximately $125 billion in 2026, while NEBIUS is expected to surge to around $33 billion, indicating both are on a hyper-growth trajectory.</p>\n<p>A key differentiator for investors is the nature of their revenue streams. Over 98% of CoreWeave, Inc.'s business is tied to multi-year \"take-or-pay\" long-term contracts, providing strong revenue visibility. Conversely, NEBIUS has a higher exposure to the spot market, which could offer greater near-term pricing flexibility in an environment of rising GPU prices. Excluding contracts with Microsoft and Meta, approximately $550 million of NEBIUS's Annual Recurring Revenue (ARR) comes from on-demand/spot markets and shorter-term contracts. This provides significant repricing potential amid strong demand and constrained supply. Factors supporting near-term GPU pricing strength include robust demand, supply bottlenecks, memory price inflation, and a surge in token consumption driven by autonomous agents.</p>\n<p>In the spot market exposure dynamic, NEBIUS holds an advantage and may benefit more from near-term GPU price increases. The aforementioned $550 million ARR is largely subject to repricing. In contrast, CoreWeave, Inc.'s long-term contracts lock in revenue visibility but sacrifice spot market elasticity. It is noted that memory price increases, deployment challenges, and rising compute consumption from autonomous agents are likely to sustain strong GPU pricing trends in the short term. If GPU prices continue to climb, NEBIUS could consistently outperform.</p>\n<p>Regarding data center strategy, both CoreWeave, Inc. and NEBIUS employ a \"hybrid\" approach, combining co-location, build-to-suit, and self-built facilities, but their existing infrastructure differs significantly. CoreWeave, Inc. currently operates 43 data centers, predominantly using a co-location model, but is actively introducing self-build and joint venture models. NEBIUS already operates a 75MW self-built data center in Finland and has planned large-scale projects in the US. NEBIUS views self-built campuses as the long-term optimal solution for cost control and operational efficiency. Both companies utilize co-location for rapid expansion but plan to increase self-build ownership for better economics and control.</p>\n<p>Power capacity is a core resource in the AI cloud competition. As of the end of 2025, CoreWeave, Inc. had secured 3.1GW of power capacity, with over 850MW active. NEBIUS had secured 2GW, with only 170MW active, meaning CoreWeave, Inc.'s active power is five times greater. Looking ahead, CoreWeave, Inc. aims for over 8GW of secured capacity by 2030, while NEBIUS targets 3GW by the end of 2026 and 5GW by 2030. The gap in annual capacity additions reflects CoreWeave, Inc.'s proven execution capability at scale, whereas NEBIUS's story is still in a relatively earlier stage.</p>\n<p>Capital structures and financing strategies also differ markedly. To support massive capital expenditure, both require substantial ongoing funding. CoreWeave, Inc. relies heavily on a Delayed Draw Term Loan (DDTL) mechanism, having developed a mature asset-level debt financing system. Its total debt principal reached $21.6 billion by the end of 2025, with projections suggesting significant increases through 2028. NEBIUS started with a cleaner balance sheet, utilizing convertible notes, equity issuance, and customer prepayments for financing. Its recent $4.338 billion convertible note offering has bolstered liquidity. For 2026 capital expenditure, CoreWeave, Inc. guided for $30-35 billion, while NEBIUS guided for $16-20 billion. Both have received $2 billion in strategic investment from NVIDIA.</p>\n<p>Customer concentration and market strategy reveal another contrast. CoreWeave, Inc.'s strategy prioritizes achieving maximum scale rapidly. Approximately two-thirds of its current revenue comes from Microsoft, with a similar proportion of ARR expected from Microsoft, OpenAI, and Meta combined by the end of 2026. This high concentration offers strong revenue visibility but carries concentration risk. NEBIUS's strategy focuses on selling AI cloud services to a broader base of enterprise customers and AI startups. While its current backlog is also concentrated, its anchor contracts with Microsoft and Meta are of high quality. A portion of the Meta contract provides a \"remaining capacity backstop commitment,\" giving NEBIUS flexibility to serve smaller and less creditworthy clients. NEBIUS aims to grow its ARR from its core contracts and gradually diversify its customer base.</p>\n<p>In terms of software stacks, both companies aim to be \"full-stack AI infrastructure platforms\" rather than mere GPU lessors. CoreWeave, Inc.'s software stack is more mature, particularly in infrastructure orchestration, observability, workload management, and storage. Its Object Storage business has surpassed $100 million in ARR. NEBIUS focuses on building a tightly integrated, secure AI cloud environment, emphasizing virtualization, tenant isolation, workload orchestration, and inference toolchains, aiming for a vertically integrated platform for enterprise clients. CoreWeave, Inc. leads in software maturity and platform breadth, while NEBIUS shows long-term potential with its differentiated, application-focused products.</p>\n<p>Profitability profiles start from vastly different points but may converge. CoreWeave, Inc. already demonstrates strong EBITDA profitability (60.8% margin in 2025), though its adjusted EBIT margin is expected to face temporary compression due to timing differences between capital deployment and revenue recognition. NEBIUS is currently in a significant loss-making phase, attributed to inherited operational costs, drag from loss-making assets, and depreciation/interest pressures during rapid expansion. However, NEBIUS's EBITDA margin is projected to improve dramatically from -12.2% in 2025 to over 70% by 2028. If NEBIUS can realize the cost advantages of its self-built data centers and successfully transition to higher-margin enterprise clients, its long-term profit potential is significant.</p>\n<p>Both companies face valuation challenges. A \"Neutral\" rating was assigned to each, with target prices below current trading levels, suggesting optimistic expectations are largely priced in. CoreWeave, Inc.'s primary risks include its high debt load and concentrated customer base. NEBIUS's core risks involve aggressive short-term revenue targets, an unproven profit record, and uncertainty surrounding its sales transformation towards a broader enterprise clientele. Shared potential risks include normalization of AI demand, in-sourcing of AI compute by major customers, and a shortening effective useful life of GPUs. For investors prioritizing scale and certainty, CoreWeave, Inc.'s execution and financial visibility are more appealing. For those seeking growth optionality and diversification, NEBIUS's spot market exposure and enterprise cloud strategy offer a differentiated investment thesis.</p>","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>Comparative Analysis of Emerging AI Cloud Providers: CoreWeave and Nebius</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; }\nul,ol{ margin-left:2em; }\nul{ list-style:disc; }\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nComparative Analysis of Emerging AI Cloud Providers: CoreWeave and Nebius\n</h2>\n\n<h4 class=\"meta\">\n\n\n<a class=\"head\" href=\"https://laohu8.com/wemedia/1039043262\">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://community-static.tradeup.com/news/8296859682db4b478146245e72de1922);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">Deep News </p>\n<p class=\"h-time\">2026-04-16 14:56</p>\n</div>\n\n</a>\n\n\n</h4>\n\n</header>\n<article>\n<p>A recent in-depth report provides a systematic comparison of the strategic differences and similarities between two prominent Neocloud companies, CoreWeave, Inc. and NEBIUS. According to the analysis, CoreWeave, Inc. has established a leadership position in the industry due to its larger scale, proven execution track record, and highly visible financing pathway. In contrast, NEBIUS is building differentiated optionality value through greater spot market flexibility, a diversified strategy targeting enterprise customers, and a more flexible capital structure.</p>\n<p>The disparity in financial performance is stark. In 2025, CoreWeave, Inc. reported revenue of $51.3 billion, representing a 168% year-over-year increase, with EBITDA reaching $31 billion and a margin of 60%. NEBIUS reported revenue of only $5.3 billion, a 479% year-over-year increase, but posted an EBITDA loss of $65 million, resulting in a negative margin of -12%. However, the growth rates for both companies are impressive. CoreWeave, Inc.'s revenue is projected to grow to approximately $125 billion in 2026, while NEBIUS is expected to surge to around $33 billion, indicating both are on a hyper-growth trajectory.</p>\n<p>A key differentiator for investors is the nature of their revenue streams. Over 98% of CoreWeave, Inc.'s business is tied to multi-year \"take-or-pay\" long-term contracts, providing strong revenue visibility. Conversely, NEBIUS has a higher exposure to the spot market, which could offer greater near-term pricing flexibility in an environment of rising GPU prices. Excluding contracts with Microsoft and Meta, approximately $550 million of NEBIUS's Annual Recurring Revenue (ARR) comes from on-demand/spot markets and shorter-term contracts. This provides significant repricing potential amid strong demand and constrained supply. Factors supporting near-term GPU pricing strength include robust demand, supply bottlenecks, memory price inflation, and a surge in token consumption driven by autonomous agents.</p>\n<p>In the spot market exposure dynamic, NEBIUS holds an advantage and may benefit more from near-term GPU price increases. The aforementioned $550 million ARR is largely subject to repricing. In contrast, CoreWeave, Inc.'s long-term contracts lock in revenue visibility but sacrifice spot market elasticity. It is noted that memory price increases, deployment challenges, and rising compute consumption from autonomous agents are likely to sustain strong GPU pricing trends in the short term. If GPU prices continue to climb, NEBIUS could consistently outperform.</p>\n<p>Regarding data center strategy, both CoreWeave, Inc. and NEBIUS employ a \"hybrid\" approach, combining co-location, build-to-suit, and self-built facilities, but their existing infrastructure differs significantly. CoreWeave, Inc. currently operates 43 data centers, predominantly using a co-location model, but is actively introducing self-build and joint venture models. NEBIUS already operates a 75MW self-built data center in Finland and has planned large-scale projects in the US. NEBIUS views self-built campuses as the long-term optimal solution for cost control and operational efficiency. Both companies utilize co-location for rapid expansion but plan to increase self-build ownership for better economics and control.</p>\n<p>Power capacity is a core resource in the AI cloud competition. As of the end of 2025, CoreWeave, Inc. had secured 3.1GW of power capacity, with over 850MW active. NEBIUS had secured 2GW, with only 170MW active, meaning CoreWeave, Inc.'s active power is five times greater. Looking ahead, CoreWeave, Inc. aims for over 8GW of secured capacity by 2030, while NEBIUS targets 3GW by the end of 2026 and 5GW by 2030. The gap in annual capacity additions reflects CoreWeave, Inc.'s proven execution capability at scale, whereas NEBIUS's story is still in a relatively earlier stage.</p>\n<p>Capital structures and financing strategies also differ markedly. To support massive capital expenditure, both require substantial ongoing funding. CoreWeave, Inc. relies heavily on a Delayed Draw Term Loan (DDTL) mechanism, having developed a mature asset-level debt financing system. Its total debt principal reached $21.6 billion by the end of 2025, with projections suggesting significant increases through 2028. NEBIUS started with a cleaner balance sheet, utilizing convertible notes, equity issuance, and customer prepayments for financing. Its recent $4.338 billion convertible note offering has bolstered liquidity. For 2026 capital expenditure, CoreWeave, Inc. guided for $30-35 billion, while NEBIUS guided for $16-20 billion. Both have received $2 billion in strategic investment from NVIDIA.</p>\n<p>Customer concentration and market strategy reveal another contrast. CoreWeave, Inc.'s strategy prioritizes achieving maximum scale rapidly. Approximately two-thirds of its current revenue comes from Microsoft, with a similar proportion of ARR expected from Microsoft, OpenAI, and Meta combined by the end of 2026. This high concentration offers strong revenue visibility but carries concentration risk. NEBIUS's strategy focuses on selling AI cloud services to a broader base of enterprise customers and AI startups. While its current backlog is also concentrated, its anchor contracts with Microsoft and Meta are of high quality. A portion of the Meta contract provides a \"remaining capacity backstop commitment,\" giving NEBIUS flexibility to serve smaller and less creditworthy clients. NEBIUS aims to grow its ARR from its core contracts and gradually diversify its customer base.</p>\n<p>In terms of software stacks, both companies aim to be \"full-stack AI infrastructure platforms\" rather than mere GPU lessors. CoreWeave, Inc.'s software stack is more mature, particularly in infrastructure orchestration, observability, workload management, and storage. Its Object Storage business has surpassed $100 million in ARR. NEBIUS focuses on building a tightly integrated, secure AI cloud environment, emphasizing virtualization, tenant isolation, workload orchestration, and inference toolchains, aiming for a vertically integrated platform for enterprise clients. CoreWeave, Inc. leads in software maturity and platform breadth, while NEBIUS shows long-term potential with its differentiated, application-focused products.</p>\n<p>Profitability profiles start from vastly different points but may converge. CoreWeave, Inc. already demonstrates strong EBITDA profitability (60.8% margin in 2025), though its adjusted EBIT margin is expected to face temporary compression due to timing differences between capital deployment and revenue recognition. NEBIUS is currently in a significant loss-making phase, attributed to inherited operational costs, drag from loss-making assets, and depreciation/interest pressures during rapid expansion. However, NEBIUS's EBITDA margin is projected to improve dramatically from -12.2% in 2025 to over 70% by 2028. If NEBIUS can realize the cost advantages of its self-built data centers and successfully transition to higher-margin enterprise clients, its long-term profit potential is significant.</p>\n<p>Both companies face valuation challenges. A \"Neutral\" rating was assigned to each, with target prices below current trading levels, suggesting optimistic expectations are largely priced in. CoreWeave, Inc.'s primary risks include its high debt load and concentrated customer base. NEBIUS's core risks involve aggressive short-term revenue targets, an unproven profit record, and uncertainty surrounding its sales transformation towards a broader enterprise clientele. Shared potential risks include normalization of AI demand, in-sourcing of AI compute by major customers, and a shortening effective useful life of GPUs. For investors prioritizing scale and certainty, CoreWeave, Inc.'s execution and financial visibility are more appealing. For those seeking growth optionality and diversification, NEBIUS's spot market exposure and enterprise cloud strategy offer a differentiated investment thesis.</p>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"CRWV":"CoreWeave, Inc.","CRWG":"2倍做多CRWV ETF-Leverage Shares","NBIS":"NEBIUS","CORD":"T-REX 2X INVERSE CRWV DAILY TARGET ETF","CWVX":"2倍做多CRWV ETF-Tradr","BK4116":"互联网服务与基础架构","CRWU":"2倍做多CRWV ETF-T-Rex"},"source_url":"","is_english":true,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1135864585","content_text":"A recent in-depth report provides a systematic comparison of the strategic differences and similarities between two prominent Neocloud companies, CoreWeave, Inc. and NEBIUS. According to the analysis, CoreWeave, Inc. has established a leadership position in the industry due to its larger scale, proven execution track record, and highly visible financing pathway. In contrast, NEBIUS is building differentiated optionality value through greater spot market flexibility, a diversified strategy targeting enterprise customers, and a more flexible capital structure.\nThe disparity in financial performance is stark. In 2025, CoreWeave, Inc. reported revenue of $51.3 billion, representing a 168% year-over-year increase, with EBITDA reaching $31 billion and a margin of 60%. NEBIUS reported revenue of only $5.3 billion, a 479% year-over-year increase, but posted an EBITDA loss of $65 million, resulting in a negative margin of -12%. However, the growth rates for both companies are impressive. CoreWeave, Inc.'s revenue is projected to grow to approximately $125 billion in 2026, while NEBIUS is expected to surge to around $33 billion, indicating both are on a hyper-growth trajectory.\nA key differentiator for investors is the nature of their revenue streams. Over 98% of CoreWeave, Inc.'s business is tied to multi-year \"take-or-pay\" long-term contracts, providing strong revenue visibility. Conversely, NEBIUS has a higher exposure to the spot market, which could offer greater near-term pricing flexibility in an environment of rising GPU prices. Excluding contracts with Microsoft and Meta, approximately $550 million of NEBIUS's Annual Recurring Revenue (ARR) comes from on-demand/spot markets and shorter-term contracts. This provides significant repricing potential amid strong demand and constrained supply. Factors supporting near-term GPU pricing strength include robust demand, supply bottlenecks, memory price inflation, and a surge in token consumption driven by autonomous agents.\nIn the spot market exposure dynamic, NEBIUS holds an advantage and may benefit more from near-term GPU price increases. The aforementioned $550 million ARR is largely subject to repricing. In contrast, CoreWeave, Inc.'s long-term contracts lock in revenue visibility but sacrifice spot market elasticity. It is noted that memory price increases, deployment challenges, and rising compute consumption from autonomous agents are likely to sustain strong GPU pricing trends in the short term. If GPU prices continue to climb, NEBIUS could consistently outperform.\nRegarding data center strategy, both CoreWeave, Inc. and NEBIUS employ a \"hybrid\" approach, combining co-location, build-to-suit, and self-built facilities, but their existing infrastructure differs significantly. CoreWeave, Inc. currently operates 43 data centers, predominantly using a co-location model, but is actively introducing self-build and joint venture models. NEBIUS already operates a 75MW self-built data center in Finland and has planned large-scale projects in the US. NEBIUS views self-built campuses as the long-term optimal solution for cost control and operational efficiency. Both companies utilize co-location for rapid expansion but plan to increase self-build ownership for better economics and control.\nPower capacity is a core resource in the AI cloud competition. As of the end of 2025, CoreWeave, Inc. had secured 3.1GW of power capacity, with over 850MW active. NEBIUS had secured 2GW, with only 170MW active, meaning CoreWeave, Inc.'s active power is five times greater. Looking ahead, CoreWeave, Inc. aims for over 8GW of secured capacity by 2030, while NEBIUS targets 3GW by the end of 2026 and 5GW by 2030. The gap in annual capacity additions reflects CoreWeave, Inc.'s proven execution capability at scale, whereas NEBIUS's story is still in a relatively earlier stage.\nCapital structures and financing strategies also differ markedly. To support massive capital expenditure, both require substantial ongoing funding. CoreWeave, Inc. relies heavily on a Delayed Draw Term Loan (DDTL) mechanism, having developed a mature asset-level debt financing system. Its total debt principal reached $21.6 billion by the end of 2025, with projections suggesting significant increases through 2028. NEBIUS started with a cleaner balance sheet, utilizing convertible notes, equity issuance, and customer prepayments for financing. Its recent $4.338 billion convertible note offering has bolstered liquidity. For 2026 capital expenditure, CoreWeave, Inc. guided for $30-35 billion, while NEBIUS guided for $16-20 billion. Both have received $2 billion in strategic investment from NVIDIA.\nCustomer concentration and market strategy reveal another contrast. CoreWeave, Inc.'s strategy prioritizes achieving maximum scale rapidly. Approximately two-thirds of its current revenue comes from Microsoft, with a similar proportion of ARR expected from Microsoft, OpenAI, and Meta combined by the end of 2026. This high concentration offers strong revenue visibility but carries concentration risk. NEBIUS's strategy focuses on selling AI cloud services to a broader base of enterprise customers and AI startups. While its current backlog is also concentrated, its anchor contracts with Microsoft and Meta are of high quality. A portion of the Meta contract provides a \"remaining capacity backstop commitment,\" giving NEBIUS flexibility to serve smaller and less creditworthy clients. NEBIUS aims to grow its ARR from its core contracts and gradually diversify its customer base.\nIn terms of software stacks, both companies aim to be \"full-stack AI infrastructure platforms\" rather than mere GPU lessors. CoreWeave, Inc.'s software stack is more mature, particularly in infrastructure orchestration, observability, workload management, and storage. Its Object Storage business has surpassed $100 million in ARR. NEBIUS focuses on building a tightly integrated, secure AI cloud environment, emphasizing virtualization, tenant isolation, workload orchestration, and inference toolchains, aiming for a vertically integrated platform for enterprise clients. CoreWeave, Inc. leads in software maturity and platform breadth, while NEBIUS shows long-term potential with its differentiated, application-focused products.\nProfitability profiles start from vastly different points but may converge. CoreWeave, Inc. already demonstrates strong EBITDA profitability (60.8% margin in 2025), though its adjusted EBIT margin is expected to face temporary compression due to timing differences between capital deployment and revenue recognition. NEBIUS is currently in a significant loss-making phase, attributed to inherited operational costs, drag from loss-making assets, and depreciation/interest pressures during rapid expansion. However, NEBIUS's EBITDA margin is projected to improve dramatically from -12.2% in 2025 to over 70% by 2028. If NEBIUS can realize the cost advantages of its self-built data centers and successfully transition to higher-margin enterprise clients, its long-term profit potential is significant.\nBoth companies face valuation challenges. A \"Neutral\" rating was assigned to each, with target prices below current trading levels, suggesting optimistic expectations are largely priced in. CoreWeave, Inc.'s primary risks include its high debt load and concentrated customer base. NEBIUS's core risks involve aggressive short-term revenue targets, an unproven profit record, and uncertainty surrounding its sales transformation towards a broader enterprise clientele. Shared potential risks include normalization of AI demand, in-sourcing of AI compute by major customers, and a shortening effective useful life of GPUs. For investors prioritizing scale and certainty, CoreWeave, Inc.'s execution and financial visibility are more appealing. For those seeking growth optionality and diversification, NEBIUS's spot market exposure and enterprise cloud strategy offer a differentiated investment thesis.","news_type":1,"symbols_score_info":{"CRWU":1,"CRWV":1,"NBIS":1,"CORD":1,"CRWG":1,"CWVX":1}},"isVote":1,"tweetType":1,"viewCount":219,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":502198247093016,"gmtCreate":1763616632368,"gmtModify":1763617608137,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"wish we had the option to block paywall sources. waste of time and space.","listText":"wish we had the option to block paywall sources. waste of time and space.","text":"wish we had the option to block paywall sources. waste of time and space.","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/502198247093016","repostId":"2584791975","repostType":2,"repost":{"id":"2584791975","kind":"highlight","weMediaInfo":{"introduction":"Stock Market Quotes, Business News, Financial News, Trading Ideas, and Stock Research by Professionals","home_visible":0,"media_name":"Benzinga","id":"1052270027","head_image":"https://static.tigerbbs.com/d08bf7808052c0ca9deb4e944cae32aa"},"pubTimestamp":1763587371,"share":"https://ttm.financial/m/news/2584791975?lang=en_US&edition=fundamental","pubTime":"2025-11-20 05:22","market":"us","language":"en","title":"NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ","url":"https://stock-news.laohu8.com/highlight/detail?id=2584791975","media":"Benzinga","summary":"NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ","content":"<html><body><p>NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ</p></body></html>","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; }\nul,ol{ margin-left:2em; }\nul{ list-style:disc; }\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nNVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ\n</h2>\n\n<h4 class=\"meta\">\n\n\n<div class=\"head\" \">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://static.tigerbbs.com/d08bf7808052c0ca9deb4e944cae32aa);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">Benzinga </p>\n<p class=\"h-time\">2025-11-20 05:22</p>\n</div>\n\n</div>\n\n\n</h4>\n\n</header>\n<article>\n<html><body><p>NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ</p></body></html>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"NVDA":"英伟达"},"source_url":"https://www.benzinga.com/news/earnings/25/11/48963030/nvidia-q3-data-center-revenue-up-25-qoq-gaming-revenue-down-1-qoq-professional-visualization-revenu","is_english":true,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"2584791975","content_text":"NVIDIA Q3 Data Center Revenue Up 25% QoQ, Gaming Revenue Down 1% QoQ, Professional Visualization Revenue Up 26% QoQ","news_type":1,"symbols_score_info":{"NVDA":1.5}},"isVote":1,"tweetType":1,"viewCount":435,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":303219187245272,"gmtCreate":1715063731405,"gmtModify":1715064047850,"author":{"id":"4094393627166150","authorId":"4094393627166150","name":"Tenelia","avatar":"https://community-static.tradeup.com/news/50b5b6468a92f380db091a6bd2fe4c46","crmLevel":12,"crmLevelSwitch":1,"followedFlag":false,"authorIdStr":"4094393627166150","idStr":"4094393627166150"},"themes":[],"title":"","htmlText":"hang in there. Patience.","listText":"hang in there. Patience.","text":"hang in there. Patience.","images":[{"img":"https://community-static.tradeup.com/news/cc622ff2b38030bf9fb791d5bc914b07","width":"1125","height":"1476"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/303219187245272","isVote":1,"tweetType":1,"viewCount":263,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0}],"lives":[]}