brijeshnair
2021-08-25
Great
Cerebras Systems connects its huge chips to make AI more power-efficient
免责声明：上述内容仅代表发帖人个人观点，不构成本平台的任何投资建议。
分享至
微信
复制链接
精彩评论
我们需要你的真知灼见来填补这片空白
打开APP，发表看法
APP内打开
发表看法
2
{"i18n":{"language":"zh_CN"},"detailType":1,"isChannel":false,"data":{"magic":2,"id":837391319,"tweetId":"837391319","gmtCreate":1629855759031,"gmtModify":1633681923208,"author":{"id":4092798624667290,"idStr":"4092798624667290","authorId":4092798624667290,"authorIdStr":"4092798624667290","name":"brijeshnair","avatar":"https://static.tigerbbs.com/7fd087acb258af07a4837fa64d38c77a","vip":1,"userType":1,"introduction":"","boolIsFan":false,"boolIsHead":false,"crmLevel":3,"crmLevelSwitch":0,"individualDisplayBadges":[],"fanSize":1,"starInvestorFlag":false},"themes":[],"images":[],"coverImages":[],"extraTitle":"","html":"<html><head></head><body><p>Great</p></body></html>","htmlText":"<html><head></head><body><p>Great</p></body></html>","text":"Great","highlighted":1,"essential":1,"paper":1,"likeSize":2,"commentSize":0,"repostSize":0,"favoriteSize":0,"link":"https://laohu8.com/post/837391319","repostId":2162087230,"repostType":4,"repost":{"id":"2162087230","kind":"highlight","weMediaInfo":{"introduction":"Reuters.com brings you the latest news from around the world, covering breaking news in markets, business, politics, entertainment and technology","home_visible":1,"media_name":"Reuters","id":"1036604489","head_image":"https://static.tigerbbs.com/443ce19704621c837795676028cec868"},"pubTimestamp":1629851650,"share":"https://www.laohu8.com/m/news/2162087230?lang=&edition=full","pubTime":"2021-08-25 08:34","market":"us","language":"en","title":"Cerebras Systems connects its huge chips to make AI more power-efficient","url":"https://stock-news.laohu8.com/highlight/detail?id=2162087230","media":"Reuters","summary":"Aug 24 (Reuters) - Cerebras Systems, the Silicon Valley startup making the world's largest computer ","content":"<p>Aug 24 (Reuters) - Cerebras Systems, the Silicon Valley startup making the world's largest computer chip, said on Tuesday it can now weave together almost 200 of the chips to drastically reduce the power consumed by artificial-intelligence work.</p>\n<p>Cerebras is <a href=\"https://laohu8.com/S/AONE.U\">one</a> of a number of startups making chips specifically designed for AI and aiming to challenge current market leaders Nvidia Corp and Alphabet Inc's Google. The company has raised about $475 million in venture capital and has secured deals with pharmaceutical firms GlaxoSmithKline Plc and <a href=\"https://laohu8.com/S/AZNCF\">AstraZeneca Plc</a> to use its chips to speed up drug discovery.</p>\n<p>Traditionally, hundreds or even thousands of computer chips are manufactured on a 12-inch (30 cm) silicon disc called a wafer, which is later sliced up into individual chips. Cerebras, by contrast, uses the entire wafer. The huge Cerebras chip can hold more data at once.</p>\n<p>But artificial intelligence researchers now have AI models called \"neural networks\" too big for any single chip to hold, so they must split them up across many chips. The biggest current neural networks are still only a fraction of the complexity of a human brain, but they use much more energy than human brains because the systems that run them become less power-efficient as more chips are added.</p>\n<p>Cerebras said on Wednesday that it can put together 192 of its chips to train huge neural networks, but that the power efficiency will stay the same as chips are added. In other words, Cerebras can double the amount of computing its chips do for double the power, unlike current systems that need more than twice as much power to double their computing capacity.</p>\n<p>Current AI systems \"are in the realm where you're talking about tens of megawatts of power, and you're doing it over months. You're using a the equivalent of a small city's power to train these networks,\" Cerebras Chief Executive Andrew Feldman told Reuters. \"Power is extremely important.\"</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>Cerebras Systems connects its huge chips to make AI more power-efficient</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\">\nCerebras Systems connects its huge chips to make AI more power-efficient\n</h2>\n\n<h4 class=\"meta\">\n\n\n<a class=\"head\" href=\"https://laohu8.com/wemedia/1036604489\">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://static.tigerbbs.com/443ce19704621c837795676028cec868);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">Reuters </p>\n<p class=\"h-time\">2021-08-25 08:34</p>\n</div>\n\n</a>\n\n\n</h4>\n\n</header>\n<article>\n<p>Aug 24 (Reuters) - Cerebras Systems, the Silicon Valley startup making the world's largest computer chip, said on Tuesday it can now weave together almost 200 of the chips to drastically reduce the power consumed by artificial-intelligence work.</p>\n<p>Cerebras is <a href=\"https://laohu8.com/S/AONE.U\">one</a> of a number of startups making chips specifically designed for AI and aiming to challenge current market leaders Nvidia Corp and Alphabet Inc's Google. The company has raised about $475 million in venture capital and has secured deals with pharmaceutical firms GlaxoSmithKline Plc and <a href=\"https://laohu8.com/S/AZNCF\">AstraZeneca Plc</a> to use its chips to speed up drug discovery.</p>\n<p>Traditionally, hundreds or even thousands of computer chips are manufactured on a 12-inch (30 cm) silicon disc called a wafer, which is later sliced up into individual chips. Cerebras, by contrast, uses the entire wafer. The huge Cerebras chip can hold more data at once.</p>\n<p>But artificial intelligence researchers now have AI models called \"neural networks\" too big for any single chip to hold, so they must split them up across many chips. The biggest current neural networks are still only a fraction of the complexity of a human brain, but they use much more energy than human brains because the systems that run them become less power-efficient as more chips are added.</p>\n<p>Cerebras said on Wednesday that it can put together 192 of its chips to train huge neural networks, but that the power efficiency will stay the same as chips are added. In other words, Cerebras can double the amount of computing its chips do for double the power, unlike current systems that need more than twice as much power to double their computing capacity.</p>\n<p>Current AI systems \"are in the realm where you're talking about tens of megawatts of power, and you're doing it over months. You're using a the equivalent of a small city's power to train these networks,\" Cerebras Chief Executive Andrew Feldman told Reuters. \"Power is extremely important.\"</p>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"AZN":"阿斯利康","NVDA":"英伟达","GSK":"葛兰素史克"},"is_english":true,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"2162087230","content_text":"Aug 24 (Reuters) - Cerebras Systems, the Silicon Valley startup making the world's largest computer chip, said on Tuesday it can now weave together almost 200 of the chips to drastically reduce the power consumed by artificial-intelligence work.\nCerebras is one of a number of startups making chips specifically designed for AI and aiming to challenge current market leaders Nvidia Corp and Alphabet Inc's Google. The company has raised about $475 million in venture capital and has secured deals with pharmaceutical firms GlaxoSmithKline Plc and AstraZeneca Plc to use its chips to speed up drug discovery.\nTraditionally, hundreds or even thousands of computer chips are manufactured on a 12-inch (30 cm) silicon disc called a wafer, which is later sliced up into individual chips. Cerebras, by contrast, uses the entire wafer. The huge Cerebras chip can hold more data at once.\nBut artificial intelligence researchers now have AI models called \"neural networks\" too big for any single chip to hold, so they must split them up across many chips. The biggest current neural networks are still only a fraction of the complexity of a human brain, but they use much more energy than human brains because the systems that run them become less power-efficient as more chips are added.\nCerebras said on Wednesday that it can put together 192 of its chips to train huge neural networks, but that the power efficiency will stay the same as chips are added. In other words, Cerebras can double the amount of computing its chips do for double the power, unlike current systems that need more than twice as much power to double their computing capacity.\nCurrent AI systems \"are in the realm where you're talking about tens of megawatts of power, and you're doing it over months. You're using a the equivalent of a small city's power to train these networks,\" Cerebras Chief Executive Andrew Feldman told Reuters. \"Power is extremely important.\"","news_type":1},"isVote":1,"tweetType":1,"viewCount":72,"commentLimit":10,"likeStatus":false,"favoriteStatus":false,"reportStatus":false,"symbols":[],"verified":2,"subType":0,"readableState":1,"langContent":"EN","currentLanguage":"EN","warmUpFlag":false,"orderFlag":false,"shareable":true,"causeOfNotShareable":"","featuresForAnalytics":[],"commentAndTweetFlag":false,"andRepostAutoSelectedFlag":false,"upFlag":false,"length":5,"xxTargetLangEnum":"ORIG"},"commentList":[],"isCommentEnd":true,"isTiger":false,"isWeiXinMini":false,"url":"/m/post/837391319"}
精彩评论