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2021-08-24

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Massive AI Project Will Supercharge Tesla Stock<blockquote>大规模人工智能项目将提振特斯拉股票</blockquote>

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The two-pronged goal of the event was to show off its AI progress, and to recruit of new engineers.<blockquote>这家电动汽车公司的高管周四举行了人工智能日。该活动的双重目标是展示其人工智能进步，并招募新工程师。</blockquote> Plans went awry when Tesla-bot, a 5’8” nonfunctional humanoid robot appeared on stage.<blockquote>当一个5英尺8英寸的非功能性人形机器人特斯拉机器人出现在舞台上时，计划被打乱了。</blockquote> This is why investors should consider buying buy Tesla shares anyway.<blockquote>这就是为什么投资者无论如何都应该考虑购买特斯拉股票。</blockquote> Let’s be clear. The AI day presentation was mind-blowing. Tesla engineers are aiming so high it is hard to put the scale of innovation in perspective. Lex Fridman, an acclaimed AI researcher working at MIT and often a Tesla critic characterized the event succinctly:<blockquote>让我们说清楚。人工智能日的演讲令人兴奋。特斯拉工程师的目标如此之高，以至于很难正确看待创新的规模。Lex Fridman 是一位在麻省理工学院工作的广受赞誉的人工智能研究员，也经常是特斯拉的批评者，他简洁地描述了这一事件：</blockquote> “Tesla AI day presented the most amazing real-world AI and engineering effort I have ever seen in my life.”<blockquote>“特斯拉人工智能日展示了我一生中见过的最令人惊叹的现实世界人工智能和工程成果”。</blockquote> In the past, FridmancriticizedElon Musk, Tesla’s chief executive officer for downplaying the difficulty of the full self-driving problem. In Fridman’s view, the obstacles to FSD are so daunting he didn’t believe any firm could successfully navigate the landscape within the next 5-10 years.<blockquote>过去，弗里德曼曾批评特斯拉首席执行官德隆-马斯克淡化了全自动驾驶问题的难度。在弗里德曼看来，FSD 面临的障碍如此艰巨，以至于他不相信任何一家公司能在未来 5-10 年内成功应对这一挑战。</blockquote> The Tesla AI day changed his mind. That is saying something.<blockquote>特斯拉人工智能日改变了他的想法。这说明了一些事情。</blockquote> Musk and his team completely reimagined computer vision by thinking exponentially bigger. Then they built models to collect and label the data, and a new processor to make sense of it all.<blockquote>马斯克和他的团队通过以指数级的方式思考，彻底重新想象了计算机视觉。然后，他们建立了模型来收集和标记数据，并建立了一个新的处理器来理解这一切。</blockquote> The idea of AI conjures up rooms full of computers deciphering data and making choices on the fly. In reality, Tesla still employs 1,000 engineers who manually label pedestrians and orange road cones. The latest software iteration is getting much better at auto-labeling. Musk said on Thursday that the neural network model is being completely retrained about every 2 weeks.<blockquote>人工智能的想法让人想起满屋子的计算机破译数据并即时做出选择。事实上，特斯拉仍然雇佣了1000名工程师，他们手动给行人和橙色路锥贴上标签。最新的软件迭代在自动标记方面做得更好。马斯克周四表示，神经网络模型大约每两周进行一次完全重新训练。</blockquote> Processing is certain to improve when Tesla’s Dojo computer is outfitted with the latest in-house chips designed specifically to optimize neural networks. Engineers claim these breakthrough mega chips offer 4x the performance of the current processors yet they consume 1/5 the footprint.<blockquote>当特斯拉的 Dojo 计算机配备专门为优化神经网络而设计的最新内部芯片时，处理能力肯定会得到提高。工程师声称，这些突破性的巨型芯片提供了当前处理器4倍的性能，但它们消耗的占地面积只有当前处理器的1/5。</blockquote> Fridmanbelievesthe virtuous cycle of data collection, labeling, model retraining, and redeployment will give Tesla a real fighting chance to finally solve FSD. This is potentially a $1 trillion opportunity.<blockquote>Fridman 相信数据收集、标记、模型再训练和重新部署的良性循环将为特斯拉提供最终解决 FSD 的真正战斗机会。这是一个潜在的1万亿美元的机会。</blockquote> Unfortunately, this monumental development is getting lost in&nbsp;the analysis&nbsp;of the Tesla bot.<blockquote>不幸的是，这一巨大的发展在特斯拉机器人的分析中被忽略了。</blockquote> Investors should focus.<blockquote>投资者应该集中注意力。</blockquote> Tesla is building a fully integrated AI powerhouse. Longer-term investors should consider buying any near-term weakness in its shares.<blockquote>特斯拉正在打造一个完全集成的人工智能强国。长期投资者应考虑买入其股票的任何近期疲软。</blockquote>","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>Massive AI Project Will Supercharge Tesla Stock<blockquote>大规模人工智能项目将提振特斯拉股票</blockquote></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: 12.5px; color: #7E829C; margin: 0;}\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\">\nMassive AI Project Will Supercharge Tesla Stock<blockquote>大规模人工智能项目将提振特斯拉股票</blockquote>\n</h2>\n<h4 class=\"meta\">\n\nThestreet2021-08-24 11:34\n\n</h4>\n</header>\n<article>\nTesla (TSLA)is on the verge of a game-changing breakthrough in machine learning yet the only thing people are talking about is its plan for a stupid humanoid robot.<blockquote>特斯拉（TSLA）在机器学习领域即将取得改变游戏规则的突破，但人们唯一谈论的是它对愚蠢的人形机器人的计划。</blockquote> Executives at the electric vehicle company on Thursday held an artificial intelligence day. The two-pronged goal of the event was to show off its AI progress, and to recruit of new engineers.<blockquote>这家电动汽车公司的高管周四举行了人工智能日。该活动的双重目标是展示其人工智能进步，并招募新工程师。</blockquote> Plans went awry when Tesla-bot, a 5’8” nonfunctional humanoid robot appeared on stage.<blockquote>当一个5英尺8英寸的非功能性人形机器人特斯拉机器人出现在舞台上时，计划被打乱了。</blockquote> This is why investors should consider buying buy Tesla shares anyway.<blockquote>这就是为什么投资者无论如何都应该考虑购买特斯拉股票。</blockquote> Let’s be clear. The AI day presentation was mind-blowing. Tesla engineers are aiming so high it is hard to put the scale of innovation in perspective. Lex Fridman, an acclaimed AI researcher working at MIT and often a Tesla critic characterized the event succinctly:<blockquote>让我们说清楚。人工智能日的演讲令人兴奋。特斯拉工程师的目标如此之高，以至于很难正确看待创新的规模。Lex Fridman 是一位在麻省理工学院工作的广受赞誉的人工智能研究员，也经常是特斯拉的批评者，他简洁地描述了这一事件：</blockquote> “Tesla AI day presented the most amazing real-world AI and engineering effort I have ever seen in my life.”<blockquote>“特斯拉人工智能日展示了我一生中见过的最令人惊叹的现实世界人工智能和工程成果”。</blockquote> In the past, FridmancriticizedElon Musk, Tesla’s chief executive officer for downplaying the difficulty of the full self-driving problem. In Fridman’s view, the obstacles to FSD are so daunting he didn’t believe any firm could successfully navigate the landscape within the next 5-10 years.<blockquote>过去，弗里德曼曾批评特斯拉首席执行官德隆-马斯克淡化了全自动驾驶问题的难度。在弗里德曼看来，FSD 面临的障碍如此艰巨，以至于他不相信任何一家公司能在未来 5-10 年内成功应对这一挑战。</blockquote> The Tesla AI day changed his mind. That is saying something.<blockquote>特斯拉人工智能日改变了他的想法。这说明了一些事情。</blockquote> Musk and his team completely reimagined computer vision by thinking exponentially bigger. Then they built models to collect and label the data, and a new processor to make sense of it all.<blockquote>马斯克和他的团队通过以指数级的方式思考，彻底重新想象了计算机视觉。然后，他们建立了模型来收集和标记数据，并建立了一个新的处理器来理解这一切。</blockquote> The idea of AI conjures up rooms full of computers deciphering data and making choices on the fly. In reality, Tesla still employs 1,000 engineers who manually label pedestrians and orange road cones. The latest software iteration is getting much better at auto-labeling. Musk said on Thursday that the neural network model is being completely retrained about every 2 weeks.<blockquote>人工智能的想法让人想起满屋子的计算机破译数据并即时做出选择。事实上，特斯拉仍然雇佣了1000名工程师，他们手动给行人和橙色路锥贴上标签。最新的软件迭代在自动标记方面做得更好。马斯克周四表示，神经网络模型大约每两周进行一次完全重新训练。</blockquote> Processing is certain to improve when Tesla’s Dojo computer is outfitted with the latest in-house chips designed specifically to optimize neural networks. Engineers claim these breakthrough mega chips offer 4x the performance of the current processors yet they consume 1/5 the footprint.<blockquote>当特斯拉的 Dojo 计算机配备专门为优化神经网络而设计的最新内部芯片时，处理能力肯定会得到提高。工程师声称，这些突破性的巨型芯片提供了当前处理器4倍的性能，但它们消耗的占地面积只有当前处理器的1/5。</blockquote> Fridmanbelievesthe virtuous cycle of data collection, labeling, model retraining, and redeployment will give Tesla a real fighting chance to finally solve FSD. This is potentially a $1 trillion opportunity.<blockquote>Fridman 相信数据收集、标记、模型再训练和重新部署的良性循环将为特斯拉提供最终解决 FSD 的真正战斗机会。这是一个潜在的1万亿美元的机会。</blockquote> Unfortunately, this monumental development is getting lost in&nbsp;the analysis&nbsp;of the Tesla bot.<blockquote>不幸的是，这一巨大的发展在特斯拉机器人的分析中被忽略了。</blockquote> Investors should focus.<blockquote>投资者应该集中注意力。</blockquote> Tesla is building a fully integrated AI powerhouse. Longer-term investors should consider buying any near-term weakness in its shares.<blockquote>特斯拉正在打造一个完全集成的人工智能强国。长期投资者应考虑买入其股票的任何近期疲软。</blockquote>\n<div class=\"bt-text\">\n\n\n 来源：<a href=\"https://www.thestreet.com/tech/news/teslajdm082321\">Thestreet</a>\n为提升您的阅读体验，我们对本页面进行了排版优化\n\n\n</div>\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"TSLA":"特斯拉"},"source_url":"https://www.thestreet.com/tech/news/teslajdm082321","is_english":true,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1183887279","content_text":"Tesla (TSLA)is on the verge of a game-changing breakthrough in machine learning yet the only thing people are talking about is its plan for a stupid humanoid robot.\nExecutives at the electric vehicle company on Thursday held an artificial intelligence day. The two-pronged goal of the event was to show off its AI progress, and to recruit of new engineers.\nPlans went awry when Tesla-bot, a 5’8” nonfunctional humanoid robot appeared on stage.\nThis is why investors should consider buying buy Tesla shares anyway.\nLet’s be clear. The AI day presentation was mind-blowing. Tesla engineers are aiming so high it is hard to put the scale of innovation in perspective. Lex Fridman, an acclaimed AI researcher working at MIT and often a Tesla critic characterized the event succinctly:\n“Tesla AI day presented the most amazing real-world AI and engineering effort I have ever seen in my life.”\nIn the past, FridmancriticizedElon Musk, Tesla’s chief executive officer for downplaying the difficulty of the full self-driving problem. In Fridman’s view, the obstacles to FSD are so daunting he didn’t believe any firm could successfully navigate the landscape within the next 5-10 years.\nThe Tesla AI day changed his mind. That is saying something.\nMusk and his team completely reimagined computer vision by thinking exponentially bigger. Then they built models to collect and label the data, and a new processor to make sense of it all.\nThe idea of AI conjures up rooms full of computers deciphering data and making choices on the fly. In reality, Tesla still employs 1,000 engineers who manually label pedestrians and orange road cones. The latest software iteration is getting much better at auto-labeling. Musk said on Thursday that the neural network model is being completely retrained about every 2 weeks.\nProcessing is certain to improve when Tesla’s Dojo computer is outfitted with the latest in-house chips designed specifically to optimize neural networks. Engineers claim these breakthrough mega chips offer 4x the performance of the current processors yet they consume 1/5 the footprint.\nFridmanbelievesthe virtuous cycle of data collection, labeling, model retraining, and redeployment will give Tesla a real fighting chance to finally solve FSD. This is potentially a $1 trillion opportunity.\nUnfortunately, this monumental development is getting lost in the analysis of the Tesla bot.\nInvestors should focus.\nTesla is building a fully integrated AI powerhouse. Longer-term investors should consider buying any near-term weakness in its shares.","news_type":1,"symbols_score_info":{"TSLA":0.9}},"isVote":1,"tweetType":1,"viewCount":2266,"commentLimit":10,"likeStatus":false,"favoriteStatus":false,"reportStatus":false,"symbols":["IRBT"],"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":6,"xxTargetLangEnum":"ORIG"},"commentList":[],"isCommentEnd":true,"isTiger":false,"isWeiXinMini":false,"url":"/m/post/834165376"}