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2021-09-09
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Facebook building custom chips for machine learning, video quality - report
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More than 100 people are working on the machine-learning chip, according to the report.</p>\n<p>The goal is to produce more powerful and power-efficient chips that will be cheaper and offer more savings in the long run for companies running power-hungry data centers. And development cost for the new chips is relatively small.</p>\n<p>It would also reduce Facebook's reliance on existing chip vendors, recently including <a href=\"https://laohu8.com/S/INTC\">Intel</a>(NASDAQ:INTC), <a href=\"https://laohu8.com/S/QCOM\">Qualcomm</a>(NASDAQ:QCOM)and <a href=\"https://laohu8.com/S/AVGO\">Broadcom</a>(NASDAQ:AVGO).</p>\n<p>Facebook has brought in engineers to work on chips previously but they focused on modifying existing designs with the outside semiconductor companies, and the ambition then was semi-custom ASICs rather than solo work on full-fledged semiconductors.</p>\n<p>But Facebook pointed the way to this outcome in previous commentary, where it noted that inference and transcoding were among its fastest growing services, and that it wouldn't be able to meet its data center needs with general-purpose processors alone.</p>\n<p>And it joins a powerful list, as Google (GOOG,GOOGL), <a href=\"https://laohu8.com/S/AMZN\">Amazon.com</a>(NASDAQ:AMZN)and <a href=\"https://laohu8.com/S/MSFT\">Microsoft</a>(NASDAQ:MSFT)have all been investing in custom silicon in order to wring better savings and performance out of their computing. Google is reportedlyconstructing its own chips for Chromebooks and Chrome devices, building on plans to use custom silicon in its phones.</p>\n<p>Facebook edged higher in early trading.</p>\n<p><img src=\"https://static.tigerbbs.com/a5a9243d1a81822969fa253931c34983\" tg-width=\"1154\" tg-height=\"553\" width=\"100%\" height=\"auto\"></p>","source":"seekingalpha","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>Facebook building custom chips for machine learning, video quality - report</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\">\nFacebook building custom chips for machine learning, video quality - report\n</h2>\n\n<h4 class=\"meta\">\n\n\n2021-09-09 22:28 GMT+8 <a href=https://seekingalpha.com/news/3738346-facebook-building-custom-chips-for-machine-learning-video-quality-report><strong>seekingalpha</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>Facebook hasjoined the big-tech party for developing in-house semiconductors, in what has become a high-stakes arms race to innovate on artificial intelligence and machine learning.\nThe social-media ...</p>\n\n<a href=\"https://seekingalpha.com/news/3738346-facebook-building-custom-chips-for-machine-learning-video-quality-report\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{},"source_url":"https://seekingalpha.com/news/3738346-facebook-building-custom-chips-for-machine-learning-video-quality-report","is_english":true,"share_image_url":"https://static.laohu8.com/5a36db9d73b4222bc376d24ccc48c8a4","article_id":"1171758120","content_text":"Facebook hasjoined the big-tech party for developing in-house semiconductors, in what has become a high-stakes arms race to innovate on artificial intelligence and machine learning.\nThe social-media giant is building a chip to power machine learning that it uses to recommend content to users, The Information reports, and is working on another to improve video transcoding quality. More than 100 people are working on the machine-learning chip, according to the report.\nThe goal is to produce more powerful and power-efficient chips that will be cheaper and offer more savings in the long run for companies running power-hungry data centers. And development cost for the new chips is relatively small.\nIt would also reduce Facebook's reliance on existing chip vendors, recently including Intel(NASDAQ:INTC), Qualcomm(NASDAQ:QCOM)and Broadcom(NASDAQ:AVGO).\nFacebook has brought in engineers to work on chips previously but they focused on modifying existing designs with the outside semiconductor companies, and the ambition then was semi-custom ASICs rather than solo work on full-fledged semiconductors.\nBut Facebook pointed the way to this outcome in previous commentary, where it noted that inference and transcoding were among its fastest growing services, and that it wouldn't be able to meet its data center needs with general-purpose processors alone.\nAnd it joins a powerful list, as Google (GOOG,GOOGL), Amazon.com(NASDAQ:AMZN)and Microsoft(NASDAQ:MSFT)have all been investing in custom silicon in order to wring better savings and performance out of their computing. Google is reportedlyconstructing its own chips for Chromebooks and Chrome devices, building on plans to use custom silicon in its phones.\nFacebook edged higher in early trading.","news_type":1},"isVote":1,"tweetType":1,"viewCount":81,"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":4,"xxTargetLangEnum":"ORIG"},"commentList":[],"isCommentEnd":true,"isTiger":false,"isWeiXinMini":false,"url":"/m/post/883944281"}
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