alvin240576 personal page - To The Moon

alvin240576

alvin240576

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11-02

$英伟达(NVDA)$

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03-09

[开心]

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02-09

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$Vista Oil & Gas, S.A.B. de C.V.(VIST)$

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23:33","market":"fut","language":"zh","title":"两年来最大力度减产！OPEC+减产200万桶/日，不再逐月开会","url":"https://stock-news.laohu8.com/highlight/detail?id=1106617054","media":"华尔街见闻","summary":"OPEC+减产200万桶/日，该目标是为11月和12月石油供应制定的。减产决议对全球原油供应的影响将小于标题数字，因为几个国家的石油产量已经远低于其配额，分析计算实际减产规模为约88万桶/日。OPEC","content":"<html><head></head><body><blockquote>OPEC+减产200万桶/日，该目标是为11月和12月石油供应制定的。减产决议对全球原油供应的影响将小于标题数字，因为几个国家的石油产量已经远低于其配额，分析计算实际减产规模为约88万桶/日。OPEC+将于11月份举行下一次会议。市场人士指出，OPEC+减产激怒美国。</blockquote><p>周三，<b>OPEC+联合部长级监督委员会（JMMC）提议减产200万桶/日。</b>上日媒体就透露，沙特和俄罗斯推动减产100万至200万桶/日甚至更多，沙特寻求在OPEC+会议上推高油价。</p><p>受JMMC消息推动，油价盘中继续上涨，美油、布油涨幅超1%。本周前两日，油价连续大涨。</p><p>产油国部长们在周三晚些时候的会议上讨论了上述提议，做出最终减产200万桶/日的政策决定。<b>OPEC+的目标是为11月和12月石油供应制定的。这是OPEC+自2020年新冠疫情开始时同意大幅减产以来的最大力度减产。</b></p><p>减产决议对全球原油供应的影响将小于标题数字所暗示的，因为几个国家的石油产量已经远低于其配额。这意味着他们已经符合新的限制，而不必减少产量。伊朗石油部副部长Amir Hossein Zamaninia表示，每日减产200万桶的基准线与之前的OPEC+协议相同。OPEC+成员国之间按比例分摊，这意味着只需要八个国家来控制实际产量，<b>分析计算实际减产规模为约88万桶/日。</b></p><p>OPEC+在新闻发布会上表示，<b>OPEC+不会再逐月开会，OPEC+的联合部长级监督委员会将每两个月开会一次。一名代表称，OPEC+将于11月份举行下一次会议。</b></p><p>沙特在10月份OPEC+会议上给出的目标是，调整为11-12月产油1050万桶/日。</p><p>俄罗斯副总理Novak表示，OPEC+同意加强合作协议，直至2023年年底。此外他还提及，油价上限可能会造成俄罗斯临时性地减产石油。</p><p>尼日利亚石油部长表示，OPEC+希望油价处于90美元/桶附近，需要采取行动，以确保油价维持在90美元。</p><p><b>OPEC的减产反映出石油生产国们对全球经济放缓的担忧。</b>当前多国央行迅速收紧货币政策以对抗通胀，这令经济受损，市场的信心不足，此外叠加美元强势，油价自年内高点大幅回落。今年早些时候，在俄乌冲突爆发后，布伦特原油一度飙升至每桶125美元以上，9月底时则一度回吐了2月以来的全部涨幅，跌至80美元一线。周三，布油位于92美元的水平。</p><p>在此前9月的会议上，OPEC+表示，该组织将从10月起减产10万桶/天，使供应量回到8月份的水平，这推翻了OPEC+前个月宣布的9月增产计划，也意味着拜登的沙特之行成果为零。上月的减产也是该组织2021年初以来的首次减产。OPEC+的这一举动出乎意料，不过由于幅度小，市场将其定性为“象征性”减产。沙特方面随后表态，称后续将保持产油政策的主动性。</p><p>OPEC的大规模减产决定，可能会给欧美等国的高能源成本驱动下的通胀斗争，增加冲击。</p><p><b>市场人士指出，OPEC+减产激怒美国，有利于俄罗斯。</b>拜登寻求在11月的中期选举之前，令油价走低。媒体称周三早些时候，美国官员们曾试图阻挠OPEC+减产行动。OPEC+减产消息公布后，拜登表示，OPEC+没必要减产石油。美国国务卿布林肯表示，拜登政府正试图确保有效的能源供应。</p><p>阿拉伯联合酋长国能源部长Suhail Al Mazrouei表示，减产决定是技术性的，而不是政治性的。重要的是要看等式的技术方面，看看对经济和经济状况的任何担忧。</p><p>美国随后可能会出台反制措施，包括额外释放石油储备，部分产品禁运等。白宫据称已经要求美国能源部分析禁止出口汽油、柴油和其他精炼石油产品是否会降低价格。这是一个有争议的想法，但在拜登政府内部正在获得部分人员的关注。</p></body></html>","source":"wallstreetcn_api","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>两年来最大力度减产！OPEC+减产200万桶/日，不再逐月开会</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\">\n两年来最大力度减产！OPEC+减产200万桶/日，不再逐月开会\n</h2>\n\n<h4 class=\"meta\">\n\n\n2022-10-05 23:33 北京时间&nbsp;&nbsp;&nbsp;<a href=https://wallstreetcn.com/articles/3671790><strong>华尔街见闻</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>OPEC+减产200万桶/日，该目标是为11月和12月石油供应制定的。减产决议对全球原油供应的影响将小于标题数字，因为几个国家的石油产量已经远低于其配额，分析计算实际减产规模为约88万桶/日。OPEC+将于11月份举行下一次会议。市场人士指出，OPEC+减产激怒美国。周三，OPEC+联合部长级监督委员会（JMMC）提议减产200万桶/日。上日媒体就透露，沙特和俄罗斯推动减产100万至200万桶/日...</p>\n\n<a href=\"https://wallstreetcn.com/articles/3671790\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/cdc7ca9eb3fdcde7868d42c981e73b12","relate_stocks":{},"source_url":"https://wallstreetcn.com/articles/3671790","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1106617054","content_text":"OPEC+减产200万桶/日，该目标是为11月和12月石油供应制定的。减产决议对全球原油供应的影响将小于标题数字，因为几个国家的石油产量已经远低于其配额，分析计算实际减产规模为约88万桶/日。OPEC+将于11月份举行下一次会议。市场人士指出，OPEC+减产激怒美国。周三，OPEC+联合部长级监督委员会（JMMC）提议减产200万桶/日。上日媒体就透露，沙特和俄罗斯推动减产100万至200万桶/日甚至更多，沙特寻求在OPEC+会议上推高油价。受JMMC消息推动，油价盘中继续上涨，美油、布油涨幅超1%。本周前两日，油价连续大涨。产油国部长们在周三晚些时候的会议上讨论了上述提议，做出最终减产200万桶/日的政策决定。OPEC+的目标是为11月和12月石油供应制定的。这是OPEC+自2020年新冠疫情开始时同意大幅减产以来的最大力度减产。减产决议对全球原油供应的影响将小于标题数字所暗示的，因为几个国家的石油产量已经远低于其配额。这意味着他们已经符合新的限制，而不必减少产量。伊朗石油部副部长Amir Hossein Zamaninia表示，每日减产200万桶的基准线与之前的OPEC+协议相同。OPEC+成员国之间按比例分摊，这意味着只需要八个国家来控制实际产量，分析计算实际减产规模为约88万桶/日。OPEC+在新闻发布会上表示，OPEC+不会再逐月开会，OPEC+的联合部长级监督委员会将每两个月开会一次。一名代表称，OPEC+将于11月份举行下一次会议。沙特在10月份OPEC+会议上给出的目标是，调整为11-12月产油1050万桶/日。俄罗斯副总理Novak表示，OPEC+同意加强合作协议，直至2023年年底。此外他还提及，油价上限可能会造成俄罗斯临时性地减产石油。尼日利亚石油部长表示，OPEC+希望油价处于90美元/桶附近，需要采取行动，以确保油价维持在90美元。OPEC的减产反映出石油生产国们对全球经济放缓的担忧。当前多国央行迅速收紧货币政策以对抗通胀，这令经济受损，市场的信心不足，此外叠加美元强势，油价自年内高点大幅回落。今年早些时候，在俄乌冲突爆发后，布伦特原油一度飙升至每桶125美元以上，9月底时则一度回吐了2月以来的全部涨幅，跌至80美元一线。周三，布油位于92美元的水平。在此前9月的会议上，OPEC+表示，该组织将从10月起减产10万桶/天，使供应量回到8月份的水平，这推翻了OPEC+前个月宣布的9月增产计划，也意味着拜登的沙特之行成果为零。上月的减产也是该组织2021年初以来的首次减产。OPEC+的这一举动出乎意料，不过由于幅度小，市场将其定性为“象征性”减产。沙特方面随后表态，称后续将保持产油政策的主动性。OPEC的大规模减产决定，可能会给欧美等国的高能源成本驱动下的通胀斗争，增加冲击。市场人士指出，OPEC+减产激怒美国，有利于俄罗斯。拜登寻求在11月的中期选举之前，令油价走低。媒体称周三早些时候，美国官员们曾试图阻挠OPEC+减产行动。OPEC+减产消息公布后，拜登表示，OPEC+没必要减产石油。美国国务卿布林肯表示，拜登政府正试图确保有效的能源供应。阿拉伯联合酋长国能源部长Suhail Al Mazrouei表示，减产决定是技术性的，而不是政治性的。重要的是要看等式的技术方面，看看对经济和经济状况的任何担忧。美国随后可能会出台反制措施，包括额外释放石油储备，部分产品禁运等。白宫据称已经要求美国能源部分析禁止出口汽油、柴油和其他精炼石油产品是否会降低价格。这是一个有争议的想法，但在拜登政府内部正在获得部分人员的关注。","news_type":1},"isVote":1,"tweetType":1,"viewCount":165,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":9916493080,"gmtCreate":1664665686940,"gmtModify":1676537489276,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"👍👍","listText":"👍👍","text":"👍👍","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":2,"commentSize":1,"repostSize":0,"link":"https://ttm.financial/post/9916493080","repostId":"1150155136","repostType":4,"repost":{"id":"1150155136","pubTimestamp":1664616181,"share":"https://ttm.financial/m/news/1150155136?lang=&edition=fundamental","pubTime":"2022-10-01 17:23","market":"us","language":"zh","title":"特斯拉AI Day 2022全解读：能走会动的Tesla Bot，DOJO超算明年量产、还有FSD新进展","url":"https://stock-news.laohu8.com/highlight/detail?id=1150155136","media":"电动星球News","summary":"几个小时前，特斯拉正式举办了 2022 AI Day，一场全球汽车、人工智能、信息科技行业翘首以待足足 13 个月的发布会。严格意义上 AI Day 不像是「发布会」，而是「交流会」——马斯克本人也在","content":"<html><head></head><body><p>几个小时前，<a href=\"https://laohu8.com/S/TSLA\">特斯拉</a>正式举办了 2022 AI Day，一场全球汽车、人工<a href=\"https://laohu8.com/S/5RE.SI\">智能</a>、信息科技行业翘首以待足足 13 个月的发布会。</p><p><img src=\"https://static.tigerbbs.com/0b8803475646fc32fd19f6657d5112fe\" tg-width=\"1080\" tg-height=\"610\" referrerpolicy=\"no-referrer\"/></p><p>严格意义上 AI Day 不像是「发布会」，而是「交流会」——马斯克本人也在推特上说，<b>「此活动旨在招聘 AI 和<a href=\"https://laohu8.com/S/300024\">机器人</a>工程师，因此技术含量很高」</b>——换句话说，这是马斯克的高山流水，为特斯拉的锺子期而开。</p><p>不过这并不妨碍我们以比较轻松的视角，记录下这场科技狂欢。因为特斯拉团队几乎 100% 实现了去年的承诺，在本届 AI Day 上带来了以下技术成果：</p><p><b>不再需要群演的真·Tesla Bot 机器人原型机；</b></p><p><b>不再停留在 PPT 的 DOJO POD 人工智能超级计算机；</b></p><p><b>FSD 技术新进展，等等。</b></p><p>当然，即使我们会尽力写得简单点，今天的文章依然会相对硬核。趁着国庆假期，建议大家可以慢慢看，下面马上开始。</p><p><b>一、Tesla Bot 原型机</b></p><p>Optimus 它来了！</p><p><img src=\"https://static.tigerbbs.com/dab53fdbd457f788ef39a1d9919389ec\" tg-width=\"1080\" tg-height=\"616\" referrerpolicy=\"no-referrer\"/></p><p>13 个月前还需要群演的 Tesla Bot，今天正式以原型机的形式出现——原型意思是<b>它还没穿衣服（外壳）</b>。</p><p><img src=\"https://static.tigerbbs.com/fcaee2a3239269a6af58a05db6ac8417\" tg-width=\"1080\" tg-height=\"561\" referrerpolicy=\"no-referrer\"/></p><p>原型机的样子比 PPT 里面明显更粗放，线束、促动器等零件堆砌略显凌乱。但好消息是，Tesla Bot 原型机已经可以走路、打招呼，双手可以完整举过头顶。</p><p><img src=\"https://static.tigerbbs.com/7a2b705c19e93a543e6cc3a1c7e0c37c\" tg-width=\"1080\" tg-height=\"607\" referrerpolicy=\"no-referrer\"/></p><p>在特斯拉的演示视频里，Optimus 已经可以做一些简单的工作，比如搬运箱子、浇花等等。</p><p><img src=\"https://static.tigerbbs.com/1f19762e88d3920e9a4ada708cb6d1f6\" tg-width=\"1080\" tg-height=\"611\" referrerpolicy=\"no-referrer\"/><img src=\"https://static.tigerbbs.com/bfb1c944c5b881d14db28c8f4604b0c2\" tg-width=\"1080\" tg-height=\"611\" referrerpolicy=\"no-referrer\"/><img src=\"https://static.tigerbbs.com/5b534c9c811249fa97342b12691d049b\" tg-width=\"1080\" tg-height=\"611\" referrerpolicy=\"no-referrer\"/></p><p>但更重要的可能是这个画面：Optimus 眼中的世界，<b>通过纯视觉发现并分析周边的一切，然后识别出自己的任务对象。</b></p><p><img src=\"https://static.tigerbbs.com/af0b4407ea6333fe710b73444f74d19c\" tg-width=\"1080\" tg-height=\"605\" referrerpolicy=\"no-referrer\"/></p><p>事实上 Optimus 不是不能装上外壳，但出于工程原因，带外壳版本截止到发布会当天还不能自如地走路（原因后面再解释），只能简单挥舞一下手臂。</p><p><img src=\"https://static.tigerbbs.com/d3544fb2099584436950ca53ffce6023\" tg-width=\"1080\" tg-height=\"614\" referrerpolicy=\"no-referrer\"/></p><p>装上外壳之后我们发现，更接近量产版的 Optimus，变得更胖了——现在它重 73 公斤，比去年 PPT 版「增重」超过 20%，整个「人」圆了一大圈。</p><p><img src=\"https://static.tigerbbs.com/0c2e0f15bfe1b7939ed6fae7f16a0619\" tg-width=\"1080\" tg-height=\"612\" referrerpolicy=\"no-referrer\"/></p><p>更接近量产，也意味着 Optimus 更高阶的参数也可以公布了：<b>100W 静坐功耗、500W 快步走功耗、超过 200 档的关节自由度，光手部自由度就有 27 档。</b></p><p><img src=\"https://static.tigerbbs.com/039afba7177cebbdc4ed877be352b7cf\" tg-width=\"1080\" tg-height=\"611\" referrerpolicy=\"no-referrer\"/></p><p>另外，<b>Optimus 的大脑由单块 FSD Chip 组成，意味着算力应该是 HW3.0 的一半（72TOPS）；电池则是 52V 电压、2.3kWh 容量、内置电子电气元件的一体单元。</b></p><p>说完数字，是时候聊聊 Optimus 的研发逻辑了。</p><p><b>1. 汽车化</b></p><p>马斯克说过<b>「当你能解决自动驾驶，你就能解决现实世界中的人工智能」</b>。这句话点破了特斯拉研发 Optimus 的方法论：大量借鉴汽车研发经验。</p><p>比如借鉴汽车碰撞模拟软件，为 Optimus 编写「跌倒测试」软件。</p><p><img src=\"https://static.tigerbbs.com/d71e64fac130c88c519e38c10f7bae68\" tg-width=\"1080\" tg-height=\"614\" referrerpolicy=\"no-referrer\"/></p><p>再比如利用汽车大规模零件的生产经验，为 Optimus 挑选尽可能保证成本+效率的原材料。「我们不会用碳纤维、钛合金这样的原材料。因为它们虽然很优秀，但像肩膀这样的易损部位，制造和维修成本都太贵了」。</p><p><img src=\"https://static.tigerbbs.com/4a952bb18e0a7d3cd21f635e72bd6f55\" tg-width=\"1080\" tg-height=\"613\" referrerpolicy=\"no-referrer\"/></p><p>除此以外，制造 Optimus 的中心思想，也基本和智能汽车相当：减少线束长度、计算和电子控制单元中心化，等等。</p><p><b>2. 仿生学</b></p><p>既然是类人机器人 humanoid，设计自然要借鉴人类仿生学。</p><p><img src=\"https://static.tigerbbs.com/2059ba8af7bd4a74564e19e5a7a0c3fd\" tg-width=\"1080\" tg-height=\"594\" referrerpolicy=\"no-referrer\"/></p><p>特斯拉用了几个例子解释 Optimus 的仿生学，首先是膝关节。特斯拉表示 Optimus 的关节希望尽量复刻生物学上的「非线性」逻辑，也就是贴合膝关节直立到完全弯曲时的受力曲线。</p><p><img src=\"https://static.tigerbbs.com/093cc607f4e1764484894b9e63cfba7c\" tg-width=\"1080\" tg-height=\"609\" referrerpolicy=\"no-referrer\"/></p><p>为此，Optimus 的膝关节使用了类似于平面四杆机构的设计，最终发力效果会更接近人类。</p><p><img src=\"https://static.tigerbbs.com/4600fe5bc521375fed886e766ecd1fdb\" tg-width=\"1080\" tg-height=\"613\" referrerpolicy=\"no-referrer\"/></p><p>紧接着，我们创造人类文明的双手，才是 Optimus 类人之路更大的 boss。</p><p><img src=\"https://static.tigerbbs.com/6c75b0de1bfce1e9340c6f66fb8391c9\" tg-width=\"1080\" tg-height=\"611\" referrerpolicy=\"no-referrer\"/></p><p>Optimus 光手掌区域就用了 6 个促动器，具有 11 档的自由度。拥有自适应的抓握角度、20 磅（9 公斤）负荷、工具使用能力、小物件精准抓握能力等等。</p><p><img src=\"https://static.tigerbbs.com/9165625d2ab1d7f020961db4ebe149c7\" tg-width=\"1080\" tg-height=\"615\" referrerpolicy=\"no-referrer\"/></p><p>此外，Optimus 的手掌用的是「non-backdrivable」无法反向驱动的指尖促动器。学术界的看法是，这样的促动器可以提升在「开放环境」下的性能。</p><p>最后是让 Optimus 学着像人类一样走路——这里用到的仿生学设计叫做「运动重心控制」。</p><p><img src=\"https://static.tigerbbs.com/5f52fd071ef0d384851c030a69d683a4\" tg-width=\"1080\" tg-height=\"614\" referrerpolicy=\"no-referrer\"/></p><p>为什么有外壳的  Optimus 还不会走？其中一个原因就是重量变了，运动重心控制算法需要重新调试。</p><p><img src=\"https://static.tigerbbs.com/d7b2784fc70757f11b9e6cc0a0c727c6\" tg-width=\"1080\" tg-height=\"614\" referrerpolicy=\"no-referrer\"/></p><p>事实上，Optimus 不仅要做到会走路，还要做到别摔倒。所以它不仅需要控制走路的重心，还要稳住受到外力（比如推搡）时的随机动态重心。</p><p><img src=\"https://static.tigerbbs.com/d525cbf7fdbcc36b915b30db5eff613d\" tg-width=\"1080\" tg-height=\"611\" referrerpolicy=\"no-referrer\"/></p><p><b>训练 FSD 用到的神经网络和在线仿真模拟</b>，这次在 Optimus 身上大显身手。<b>路径规划、视觉融合、视觉导航</b>等等熟悉的名词都被「灌输」到 Optimus 脑子里。</p><p><img src=\"https://static.tigerbbs.com/9a31fa75cdf8e5c9d09662e0d21b8c51\" tg-width=\"1080\" tg-height=\"611\" referrerpolicy=\"no-referrer\"/></p><p>这样的努力下，Optimus 今年 4 月迈出了它的第一步；7 月份解锁了骨盆活动；8 月走路时可以摆手臂了——发布会前几周，实现了脚趾离地的类人行走动作。</p><p><img src=\"https://static.tigerbbs.com/e7d02ca8c2cd350fe355c188bfb968ec\" tg-width=\"1080\" tg-height=\"614\" referrerpolicy=\"no-referrer\"/></p><p><b>3. 「肌肉」</b></p><p>我们通过结缔组织包裹着的肌肉完成运动，机器人的「肌肉」则叫做促动器 actuator。</p><p><img src=\"https://static.tigerbbs.com/de747111c66e3c5fe67ab63226333b02\" tg-width=\"1080\" tg-height=\"616\" referrerpolicy=\"no-referrer\"/></p><p>如上图所示，橙色部分均为 Optimus 的促动器，这些促动器也都是特斯拉完全自研的。</p><p><img src=\"https://static.tigerbbs.com/d5da9845173ab7eddf1c4f638e646c1f\" tg-width=\"1080\" tg-height=\"612\" referrerpolicy=\"no-referrer\"/></p><p>特斯拉为  Optimus 从力度大小的角度，设计了 6 种各自独特的促动器——这其实是很小的数字，<b>业界平均是 20-30，甚至 50 种，目的是覆盖尽可能多的人类活动细节。</b></p><p>为什么特斯拉的促动器种类这么少？原因还是 FSD 体系。</p><p>特斯拉举了 28 种人类常见活动，比如抬举手臂、弯曲右膝等。通过分析这些活动反馈的云数据，<b>找出各类运动的相对共同点，然后就可以尽量减少专门设计促动器的种类。</b></p><p><img src=\"https://static.tigerbbs.com/5e1a6c9753e3c8ab582c060fb1f3be97\" tg-width=\"1080\" tg-height=\"612\" referrerpolicy=\"no-referrer\"/></p><p>虽然只是轻描淡写的一张 PPT，但我认为促动器从 50 种减少到 6 种，意义实际上远大于借鉴特斯拉电机经验的促动器本体——<b>因为它代表着数据为王的新工业时代。</b></p><p>不过促动器种类大幅度减少，也意味着 Optimus 前期的实际效果可能会没有那么「类人」，当然还是得等最终交付了。</p><p>最后来说一个数字：<b>2 万美元</b>（约 14 万元）。</p><p>这笔钱买不到半台 Model 3，但却是马斯克口中 Optimus 的目标售价。<b>「它会彻底改变人类社会的效率，就像无人交通可以彻底改变运输效率」</b>。</p><p><b>二、DOJO 的终极形态？</b></p><p>本来发布会的第二部分是 FSD，但那部分过于硬核，我决定先让大家看点激动人心的数字。</p><p>去年 DOJO 惊艳全世界，但遗憾的是有太多细节未公布。<b>D1 芯片是怎么组成 EXA POD 超算系统的？理论性能爆炸，能代表实际应用吗？</b></p><p>这部分，特斯拉举了大量的数据，证明自己已经是计算领域的新巨头。</p><p><img src=\"https://static.tigerbbs.com/46049affe465303b965a9eae221fe1e5\" tg-width=\"1080\" tg-height=\"610\" referrerpolicy=\"no-referrer\"/></p><p><b>首先是散热。</b></p><p>先别发问号，超算平台的散热，一直是衡量超算制造者系统工程能力的重要维度。比如<a href=\"https://laohu8.com/S/GOOG\">谷歌</a>、华为、<a href=\"https://laohu8.com/S/NVDA\">英伟达</a>在公布自家方案的时候，都会花大篇幅讲散热。</p><p>DOJO POD 的散热可以用两个词概括：高集成度、高自研率。</p><p><img src=\"https://static.tigerbbs.com/bc01b3d2eb00c916972bb0f463901f65\" tg-width=\"1080\" tg-height=\"613\" referrerpolicy=\"no-referrer\"/></p><p>特斯拉在 DOJO POD 上使用了全自研的 VRM（电压调节模组），单个 VRM 模组可以在不足 25 美分硬币面积的电路上，提供超过 1000A 的电流。</p><p>高集成度带来的问题，是热膨胀系数 CTE。DOJO 堪称极限的体积集成率和发热，意味着 CTE 稍微失控，都会对系统结构造成巨大破坏（也就是会撑爆）。</p><p><img src=\"https://static.tigerbbs.com/1b89e0309fc92979fcc0544e43395e78\" tg-width=\"1080\" tg-height=\"612\" referrerpolicy=\"no-referrer\"/></p><p>为此，这套自研 VRM 在过去两年内迭代了 14 个版本，最终才完全符合特斯拉对 CTE 指标的要求。</p><p>目前 DOJO POD 已经进入负载测试阶段——单机柜 2.2MW 的负载，相当于 6 台 Model Y 双电机全力输出。</p><p><img src=\"https://static.tigerbbs.com/a690ca8342c81d44c53f98da2a5216e5\" tg-width=\"1080\" tg-height=\"618\" referrerpolicy=\"no-referrer\"/></p><p><b>解决了散热，才有资格说集成度。</b></p><p>一个 DOJO POD 机柜由两层计算托盘和存储系统组成。每一层托盘都有 6 个 D1 Tile 计算「瓦片」——两层 12 片 组成的一个机柜，就可以提供 108PFLOPS 算力的深度学习性能。</p><p><img src=\"https://static.tigerbbs.com/fefe4441c10c18928ac171726b35c75c\" tg-width=\"1080\" tg-height=\"614\" referrerpolicy=\"no-referrer\"/></p><p>对了，DOJO POD 的供电模组也是 52V 电压的，Optimus 母亲实锤了。</p><p>每层托盘都连接着超高速存储系统：640GB 运行内存可以提供超过 18TB 每秒的运算带宽，另外还有超过 1TB 每秒的网络交换。</p><p><img src=\"https://static.tigerbbs.com/4c8182aab7ef49bf1807ba3faf6decdd\" tg-width=\"1080\" tg-height=\"612\" referrerpolicy=\"no-referrer\"/></p><p>为了适配训练软件以及运营/维护，每个托盘还配备了专属的管理计算中心。</p><p><img src=\"https://static.tigerbbs.com/fb8ec92bdd51cc4895f9ad44411a3c44\" tg-width=\"1080\" tg-height=\"615\" referrerpolicy=\"no-referrer\"/></p><p>最终，可以提供<b>1.1E 算力、13TB 运存、1.3TB 缓存</b>的 EXA POD，将于 2023 年 Q1，正式量产——<b>这也是今天发布会唯一一个有确定日期的特斯拉产品。</b></p><p><img src=\"https://static.tigerbbs.com/b3130399d3b4808b0e5083b98e1877eb\" tg-width=\"1080\" tg-height=\"609\" referrerpolicy=\"no-referrer\"/></p><p>意大利炮有了，能不能轰下县城？</p><p><img src=\"https://static.tigerbbs.com/cb806e7598b3d28981907243c404eae4\" tg-width=\"1080\" tg-height=\"613\" referrerpolicy=\"no-referrer\"/></p><p>特斯拉表示，配合专属的编译器，DOJO 的训练延迟，最低可以做到同等规模 GPU 的<b>1/50！</b></p><p>最终，特斯拉的目标是到 2023 年 Q1 量产时，<b>DOJO 可以实现相比英伟达 A100，最高 4.4 倍的单芯片训练速度</b>——甚至能耗和成本都更低。</p><p><img src=\"https://static.tigerbbs.com/14920c55136e9bd5b7291378acfecdf0\" tg-width=\"1080\" tg-height=\"614\" referrerpolicy=\"no-referrer\"/></p><p><b>三、FSD 的新进化</b></p><p>文章来到这里，大家的手指应该已经划了很多次屏幕。这也说明，看到这里依然兴致勃勃的你，一定是特斯拉老粉——那就聊点更「无聊」、更硬核的吧。</p><p><img src=\"https://static.tigerbbs.com/df2d0dfc66bf889e9078c98744c779da\" tg-width=\"1080\" tg-height=\"612\" referrerpolicy=\"no-referrer\" width=\"100%\" height=\"auto\"/></p><p>篇幅有限，本届 AI Day 关于 FSD 的进展，我们只聊三个点：<b>Occupancy Network、Training Optimization、Lanes</b>。</p><p><b>1. Occupancy Network</b></p><p>先聊一个概念：矢量图。做设计的朋友一定很熟悉，这是一种精度（分辨率）可以做到无限，但占用存储空间很小的数字绘图。</p><p>Occupancy Network，就是将 3D 向量数据绘制成矢量图的、 2019 年开始兴起的一种三维重建表达方法。</p><p>有意思的是，特斯拉用了最 Occupancy Network 的方式，表达他们对 Occupancy Network 的应用：网格（方块）化的 3D 模拟。</p><p>其实 FSD 眼中的世界并不是这样 Minecraft 化的，但 Occupancy Network 的本质特征，就是用「决策边界」描绘「物体边缘」。</p><p><img src=\"https://static.tigerbbs.com/933a6dff415d2a20aca4fa2aa387f44c\" tg-width=\"1080\" tg-height=\"612\" referrerpolicy=\"no-referrer\"/></p><p>尽管 Occupancy Network 效率很高，但实际训练规模依然足够可观。目前特斯拉公布的数据是超过<b>14.4 亿帧</b>视频数据，需要超过<b>10 万个 GPU 训练小时</b>，实际视频缓存超过<b>30PB</b>——而且全程 90℃ 满负载。</p><p><img src=\"https://static.tigerbbs.com/8c5c41679c5fd2e95dc11d2a51de11ea\" tg-width=\"1080\" tg-height=\"616\" referrerpolicy=\"no-referrer\"/></p><p><b>二、因此，Training Optimization 训练优化尤为重要。</b></p><p>去年 Andrej 公布了特斯拉的千人 in-house 标注团队，今年特斯拉的重点，则在于优化自动标注流程。</p><p><img src=\"https://static.tigerbbs.com/2e04573dd50a78f4179b4a2ad9853e39\" tg-width=\"1080\" tg-height=\"615\" referrerpolicy=\"no-referrer\"/></p><p>大概总结一下就是，优化过后，训练时视频帧选取会更智能，同时大幅度减少选取的视频帧数量——<b>可以提高 30% 的训练速度</b>。</p><p><img src=\"https://static.tigerbbs.com/8ae0aee2c7838d44aedec2ba8e7b4d6d\" tg-width=\"1080\" tg-height=\"614\" referrerpolicy=\"no-referrer\"/></p><p>另外视频模型训练时 smol 异步库文件体积可以缩小 11%，所需的读取次数足足缩小到 1/4...<b>最终这套优化流程让特斯拉的 Occupancy Network 训练效率提升了 2.3 倍。</b></p><p><b>3. 最后聊聊车道线 Lanes。</b></p><p>从 FSD Beta 10.12 开始，几乎每一版更新，车道线和无保护左转，都是更新日志的第一条。</p><p><img src=\"https://static.tigerbbs.com/a0495d4d6b37869a27b1abb40423df11\" tg-width=\"1080\" tg-height=\"613\" referrerpolicy=\"no-referrer\"/></p><p>为了更准确高效应对车道线，特斯拉这次「编」了一套「属于车道的语言」。其中包括车道级别的地理几何学和拓扑几何学、车道导航、公交车道计算、多乘员车辆车道计算等等。</p><p><img src=\"https://static.tigerbbs.com/a5e8f91a38610e5c5e23fe68081b8660\" tg-width=\"1080\" tg-height=\"615\" referrerpolicy=\"no-referrer\"/></p><p><b>最终这套「车道的语言」，可以在小于 10 毫秒的延迟内，思考超过 7500 万个可能影响车辆决策的因素——而且 FSD 硬件「学会」这套语言的代价（功耗），还不足 8W。</b></p><p><img src=\"https://static.tigerbbs.com/a5e8aa95ee1c66859b5906c6ca135d4e\" tg-width=\"1080\" tg-height=\"613\" referrerpolicy=\"no-referrer\"/></p><p><b>四、四十年后，开始圆梦？</b></p><p>写到这里，我真的很头疼。</p><p>一方面是我们大部分人，都不是这届 AI Day 的对象——马斯克眼里只有招聘。另一方面，是现在一家汽车公司的发布会，对知识面要求实在太高了。</p><p><img src=\"https://static.tigerbbs.com/939520f801acf9535d7055a615bf4a47\" tg-width=\"1080\" tg-height=\"576\" referrerpolicy=\"no-referrer\"/></p><p>还是说回马斯克吧，40 年前的他，还是个每天会看 10 个小时科幻小说的小孩子，沉醉于《银河系漫游指南》、《基地》、《严厉的月亮》等等。</p><p>但正是这些科幻小说，培养了马斯克冰冷却又宏大的事业观。他会跟你说人类社会生产力的效率可以扩大到无限，他会跟你说人口是维系文明的最重要因素。</p><p>所以，当我们把 52 岁的马斯克和 12 岁的马斯克放在一起，你会发现他俩依然在本质上是同一个人。</p><p>也正因如此，你看到他如今几乎涉猎了科幻小说所有最热门题材的商业帝国，才会觉得「哦，那很正常」。</p><p>希望明年我们能看到更接近现实的马斯克童梦吧。</p></body></html>","source":"lsy1574414115752","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>特斯拉AI Day 2022全解读：能走会动的Tesla Bot，DOJO超算明年量产、还有FSD新进展</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\">\n特斯拉AI Day 2022全解读：能走会动的Tesla Bot，DOJO超算明年量产、还有FSD新进展\n</h2>\n\n<h4 class=\"meta\">\n\n\n2022-10-01 17:23 北京时间&nbsp;&nbsp;&nbsp;<a href=https://mp.weixin.qq.com/s/HRr8_Og1Y2oBBmouv0E1BA><strong>电动星球News</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>几个小时前，特斯拉正式举办了 2022 AI Day，一场全球汽车、人工智能、信息科技行业翘首以待足足 13 个月的发布会。严格意义上 AI Day 不像是「发布会」，而是「交流会」——马斯克本人也在推特上说，「此活动旨在招聘 AI 和机器人工程师，因此技术含量很高」——换句话说，这是马斯克的高山流水，为特斯拉的锺子期而开。不过这并不妨碍我们以比较轻松的视角，记录下这场科技狂欢。因为特斯拉团队几乎...</p>\n\n<a href=\"https://mp.weixin.qq.com/s/HRr8_Og1Y2oBBmouv0E1BA\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/0b8803475646fc32fd19f6657d5112fe","relate_stocks":{"BK4511":"特斯拉概念","BK4099":"汽车制造商","BK4551":"寇图资本持仓","TSLA":"特斯拉","BK4543":"AI","BK4533":"AQR资本管理(全球第二大对冲基金)","BK4528":"SaaS概念","BK4555":"新能源车","BK4534":"瑞士信贷持仓","BK4548":"巴美列捷福持仓","BK4527":"明星科技股","BK4550":"红杉资本持仓","BK4023":"应用软件","AI":"C3.ai, Inc.","BK4581":"高盛持仓","FSD":"First Trust High Income Long/Sho","BK4574":"无人驾驶"},"source_url":"https://mp.weixin.qq.com/s/HRr8_Og1Y2oBBmouv0E1BA","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1150155136","content_text":"几个小时前，特斯拉正式举办了 2022 AI Day，一场全球汽车、人工智能、信息科技行业翘首以待足足 13 个月的发布会。严格意义上 AI Day 不像是「发布会」，而是「交流会」——马斯克本人也在推特上说，「此活动旨在招聘 AI 和机器人工程师，因此技术含量很高」——换句话说，这是马斯克的高山流水，为特斯拉的锺子期而开。不过这并不妨碍我们以比较轻松的视角，记录下这场科技狂欢。因为特斯拉团队几乎 100% 实现了去年的承诺，在本届 AI Day 上带来了以下技术成果：不再需要群演的真·Tesla Bot 机器人原型机；不再停留在 PPT 的 DOJO POD 人工智能超级计算机；FSD 技术新进展，等等。当然，即使我们会尽力写得简单点，今天的文章依然会相对硬核。趁着国庆假期，建议大家可以慢慢看，下面马上开始。一、Tesla Bot 原型机Optimus 它来了！13 个月前还需要群演的 Tesla Bot，今天正式以原型机的形式出现——原型意思是它还没穿衣服（外壳）。原型机的样子比 PPT 里面明显更粗放，线束、促动器等零件堆砌略显凌乱。但好消息是，Tesla Bot 原型机已经可以走路、打招呼，双手可以完整举过头顶。在特斯拉的演示视频里，Optimus 已经可以做一些简单的工作，比如搬运箱子、浇花等等。但更重要的可能是这个画面：Optimus 眼中的世界，通过纯视觉发现并分析周边的一切，然后识别出自己的任务对象。事实上 Optimus 不是不能装上外壳，但出于工程原因，带外壳版本截止到发布会当天还不能自如地走路（原因后面再解释），只能简单挥舞一下手臂。装上外壳之后我们发现，更接近量产版的 Optimus，变得更胖了——现在它重 73 公斤，比去年 PPT 版「增重」超过 20%，整个「人」圆了一大圈。更接近量产，也意味着 Optimus 更高阶的参数也可以公布了：100W 静坐功耗、500W 快步走功耗、超过 200 档的关节自由度，光手部自由度就有 27 档。另外，Optimus 的大脑由单块 FSD Chip 组成，意味着算力应该是 HW3.0 的一半（72TOPS）；电池则是 52V 电压、2.3kWh 容量、内置电子电气元件的一体单元。说完数字，是时候聊聊 Optimus 的研发逻辑了。1. 汽车化马斯克说过「当你能解决自动驾驶，你就能解决现实世界中的人工智能」。这句话点破了特斯拉研发 Optimus 的方法论：大量借鉴汽车研发经验。比如借鉴汽车碰撞模拟软件，为 Optimus 编写「跌倒测试」软件。再比如利用汽车大规模零件的生产经验，为 Optimus 挑选尽可能保证成本+效率的原材料。「我们不会用碳纤维、钛合金这样的原材料。因为它们虽然很优秀，但像肩膀这样的易损部位，制造和维修成本都太贵了」。除此以外，制造 Optimus 的中心思想，也基本和智能汽车相当：减少线束长度、计算和电子控制单元中心化，等等。2. 仿生学既然是类人机器人 humanoid，设计自然要借鉴人类仿生学。特斯拉用了几个例子解释 Optimus 的仿生学，首先是膝关节。特斯拉表示 Optimus 的关节希望尽量复刻生物学上的「非线性」逻辑，也就是贴合膝关节直立到完全弯曲时的受力曲线。为此，Optimus 的膝关节使用了类似于平面四杆机构的设计，最终发力效果会更接近人类。紧接着，我们创造人类文明的双手，才是 Optimus 类人之路更大的 boss。Optimus 光手掌区域就用了 6 个促动器，具有 11 档的自由度。拥有自适应的抓握角度、20 磅（9 公斤）负荷、工具使用能力、小物件精准抓握能力等等。此外，Optimus 的手掌用的是「non-backdrivable」无法反向驱动的指尖促动器。学术界的看法是，这样的促动器可以提升在「开放环境」下的性能。最后是让 Optimus 学着像人类一样走路——这里用到的仿生学设计叫做「运动重心控制」。为什么有外壳的  Optimus 还不会走？其中一个原因就是重量变了，运动重心控制算法需要重新调试。事实上，Optimus 不仅要做到会走路，还要做到别摔倒。所以它不仅需要控制走路的重心，还要稳住受到外力（比如推搡）时的随机动态重心。训练 FSD 用到的神经网络和在线仿真模拟，这次在 Optimus 身上大显身手。路径规划、视觉融合、视觉导航等等熟悉的名词都被「灌输」到 Optimus 脑子里。这样的努力下，Optimus 今年 4 月迈出了它的第一步；7 月份解锁了骨盆活动；8 月走路时可以摆手臂了——发布会前几周，实现了脚趾离地的类人行走动作。3. 「肌肉」我们通过结缔组织包裹着的肌肉完成运动，机器人的「肌肉」则叫做促动器 actuator。如上图所示，橙色部分均为 Optimus 的促动器，这些促动器也都是特斯拉完全自研的。特斯拉为  Optimus 从力度大小的角度，设计了 6 种各自独特的促动器——这其实是很小的数字，业界平均是 20-30，甚至 50 种，目的是覆盖尽可能多的人类活动细节。为什么特斯拉的促动器种类这么少？原因还是 FSD 体系。特斯拉举了 28 种人类常见活动，比如抬举手臂、弯曲右膝等。通过分析这些活动反馈的云数据，找出各类运动的相对共同点，然后就可以尽量减少专门设计促动器的种类。虽然只是轻描淡写的一张 PPT，但我认为促动器从 50 种减少到 6 种，意义实际上远大于借鉴特斯拉电机经验的促动器本体——因为它代表着数据为王的新工业时代。不过促动器种类大幅度减少，也意味着 Optimus 前期的实际效果可能会没有那么「类人」，当然还是得等最终交付了。最后来说一个数字：2 万美元（约 14 万元）。这笔钱买不到半台 Model 3，但却是马斯克口中 Optimus 的目标售价。「它会彻底改变人类社会的效率，就像无人交通可以彻底改变运输效率」。二、DOJO 的终极形态？本来发布会的第二部分是 FSD，但那部分过于硬核，我决定先让大家看点激动人心的数字。去年 DOJO 惊艳全世界，但遗憾的是有太多细节未公布。D1 芯片是怎么组成 EXA POD 超算系统的？理论性能爆炸，能代表实际应用吗？这部分，特斯拉举了大量的数据，证明自己已经是计算领域的新巨头。首先是散热。先别发问号，超算平台的散热，一直是衡量超算制造者系统工程能力的重要维度。比如谷歌、华为、英伟达在公布自家方案的时候，都会花大篇幅讲散热。DOJO POD 的散热可以用两个词概括：高集成度、高自研率。特斯拉在 DOJO POD 上使用了全自研的 VRM（电压调节模组），单个 VRM 模组可以在不足 25 美分硬币面积的电路上，提供超过 1000A 的电流。高集成度带来的问题，是热膨胀系数 CTE。DOJO 堪称极限的体积集成率和发热，意味着 CTE 稍微失控，都会对系统结构造成巨大破坏（也就是会撑爆）。为此，这套自研 VRM 在过去两年内迭代了 14 个版本，最终才完全符合特斯拉对 CTE 指标的要求。目前 DOJO POD 已经进入负载测试阶段——单机柜 2.2MW 的负载，相当于 6 台 Model Y 双电机全力输出。解决了散热，才有资格说集成度。一个 DOJO POD 机柜由两层计算托盘和存储系统组成。每一层托盘都有 6 个 D1 Tile 计算「瓦片」——两层 12 片 组成的一个机柜，就可以提供 108PFLOPS 算力的深度学习性能。对了，DOJO POD 的供电模组也是 52V 电压的，Optimus 母亲实锤了。每层托盘都连接着超高速存储系统：640GB 运行内存可以提供超过 18TB 每秒的运算带宽，另外还有超过 1TB 每秒的网络交换。为了适配训练软件以及运营/维护，每个托盘还配备了专属的管理计算中心。最终，可以提供1.1E 算力、13TB 运存、1.3TB 缓存的 EXA POD，将于 2023 年 Q1，正式量产——这也是今天发布会唯一一个有确定日期的特斯拉产品。意大利炮有了，能不能轰下县城？特斯拉表示，配合专属的编译器，DOJO 的训练延迟，最低可以做到同等规模 GPU 的1/50！最终，特斯拉的目标是到 2023 年 Q1 量产时，DOJO 可以实现相比英伟达 A100，最高 4.4 倍的单芯片训练速度——甚至能耗和成本都更低。三、FSD 的新进化文章来到这里，大家的手指应该已经划了很多次屏幕。这也说明，看到这里依然兴致勃勃的你，一定是特斯拉老粉——那就聊点更「无聊」、更硬核的吧。篇幅有限，本届 AI Day 关于 FSD 的进展，我们只聊三个点：Occupancy Network、Training Optimization、Lanes。1. Occupancy Network先聊一个概念：矢量图。做设计的朋友一定很熟悉，这是一种精度（分辨率）可以做到无限，但占用存储空间很小的数字绘图。Occupancy Network，就是将 3D 向量数据绘制成矢量图的、 2019 年开始兴起的一种三维重建表达方法。有意思的是，特斯拉用了最 Occupancy Network 的方式，表达他们对 Occupancy Network 的应用：网格（方块）化的 3D 模拟。其实 FSD 眼中的世界并不是这样 Minecraft 化的，但 Occupancy Network 的本质特征，就是用「决策边界」描绘「物体边缘」。尽管 Occupancy Network 效率很高，但实际训练规模依然足够可观。目前特斯拉公布的数据是超过14.4 亿帧视频数据，需要超过10 万个 GPU 训练小时，实际视频缓存超过30PB——而且全程 90℃ 满负载。二、因此，Training Optimization 训练优化尤为重要。去年 Andrej 公布了特斯拉的千人 in-house 标注团队，今年特斯拉的重点，则在于优化自动标注流程。大概总结一下就是，优化过后，训练时视频帧选取会更智能，同时大幅度减少选取的视频帧数量——可以提高 30% 的训练速度。另外视频模型训练时 smol 异步库文件体积可以缩小 11%，所需的读取次数足足缩小到 1/4...最终这套优化流程让特斯拉的 Occupancy Network 训练效率提升了 2.3 倍。3. 最后聊聊车道线 Lanes。从 FSD Beta 10.12 开始，几乎每一版更新，车道线和无保护左转，都是更新日志的第一条。为了更准确高效应对车道线，特斯拉这次「编」了一套「属于车道的语言」。其中包括车道级别的地理几何学和拓扑几何学、车道导航、公交车道计算、多乘员车辆车道计算等等。最终这套「车道的语言」，可以在小于 10 毫秒的延迟内，思考超过 7500 万个可能影响车辆决策的因素——而且 FSD 硬件「学会」这套语言的代价（功耗），还不足 8W。四、四十年后，开始圆梦？写到这里，我真的很头疼。一方面是我们大部分人，都不是这届 AI Day 的对象——马斯克眼里只有招聘。另一方面，是现在一家汽车公司的发布会，对知识面要求实在太高了。还是说回马斯克吧，40 年前的他，还是个每天会看 10 个小时科幻小说的小孩子，沉醉于《银河系漫游指南》、《基地》、《严厉的月亮》等等。但正是这些科幻小说，培养了马斯克冰冷却又宏大的事业观。他会跟你说人类社会生产力的效率可以扩大到无限，他会跟你说人口是维系文明的最重要因素。所以，当我们把 52 岁的马斯克和 12 岁的马斯克放在一起，你会发现他俩依然在本质上是同一个人。也正因如此，你看到他如今几乎涉猎了科幻小说所有最热门题材的商业帝国，才会觉得「哦，那很正常」。希望明年我们能看到更接近现实的马斯克童梦吧。","news_type":1},"isVote":1,"tweetType":1,"viewCount":61,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":9997665379,"gmtCreate":1661810623693,"gmtModify":1676536580293,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"<a href=\"https://ttm.financial/S/BBBY\">$3B家居(BBBY)$</a>☺","listText":"<a 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&nbsp;</a>😊","listText":"<a href=\"https://ttm.financial/S/Y92.SI\">$泰国酿酒(Y92.SI)$ &nbsp;</a>😊","text":"$泰国酿酒(Y92.SI)$ 😊","images":[{"img":"https://community-static.tradeup.com/news/976684aa4ee5147b323474dada79c8fe","width":"1080","height":"2182"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":3,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/9957219517","isVote":1,"tweetType":1,"viewCount":165,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0},{"id":9952190449,"gmtCreate":1674515474981,"gmtModify":1676538943888,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"👍","listText":"👍","text":"👍","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":1,"repostSize":0,"link":"https://ttm.financial/post/9952190449","repostId":"688649304","repostType":1,"repost":{"id":688649304,"gmtCreate":1657555200000,"gmtModify":1676533330383,"author":{"id":"3570684952272154","authorId":"3570684952272154","name":"英伟达官方","avatar":"https://static.tigerbbs.com/a032ec5702e8405d9f658cdcb484031c","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"idStr":"3570684952272154","authorIdStr":"3570684952272154"},"themes":[],"title":"NVIDIA Clara 平臺助力火山引擎構建醫療健康和生命科學行業方案","htmlText":"案例簡介 隨着AI在醫療健康和生命科學領域應用的不斷增加，GPU算力的需求迅猛增長。火山引擎機器學習平臺在NVIDIA A100 Tensor Core GPU的硬件基礎架構之上，基於NVIDIA Clara 平臺構建面向醫療健康和生命科學的行業方案。通過公有云、專業工具的結合，爲企業提升開發效率。 本案例爲NVIDIA Clara 平臺，NGC（NVIDIA GPU Cloud），NVIDIA A100 Tensor Core GPU。 Case Introduction With the rapid increase of AI applications in healthcare and life science, developers’ need on GPU computation expand at very high speed. With NVIDIA A100 Tensor Core GPUs infrastructure, Volcengine adopt NVIDIA Clara platform to build professional platforms for healthcare and life science industry. &nbsp;&nbsp;&nbsp; Mainly applies to NVIDIA Clara Platform，NGC (NVIDIA GPU Cloud) and NVIDIA A100 Tensor Core GPUs. 客戶簡介及客戶挑戰 火山引擎機器學習平臺，由字節跳動應用機器學習團隊推出，支撐了抖音、西瓜視頻等產品的AI算法訓練與推理業務。目前機器學習平臺已經正式對外服務，在AI醫療、自動駕駛、AI企業服務等多個行業落地。 AI技術已經成爲醫療健康和生命科學領域發展的重要驅動力，以計算機視覺、自然","listText":"案例簡介 隨着AI在醫療健康和生命科學領域應用的不斷增加，GPU算力的需求迅猛增長。火山引擎機器學習平臺在NVIDIA A100 Tensor Core GPU的硬件基礎架構之上，基於NVIDIA Clara 平臺構建面向醫療健康和生命科學的行業方案。通過公有云、專業工具的結合，爲企業提升開發效率。 本案例爲NVIDIA Clara 平臺，NGC（NVIDIA GPU Cloud），NVIDIA A100 Tensor Core GPU。 Case Introduction With the rapid increase of AI applications in healthcare and life science, developers’ need on GPU computation expand at very high speed. With NVIDIA A100 Tensor Core GPUs infrastructure, Volcengine adopt NVIDIA Clara platform to build professional platforms for healthcare and life science industry. &nbsp;&nbsp;&nbsp; Mainly applies to NVIDIA Clara Platform，NGC (NVIDIA GPU Cloud) and NVIDIA A100 Tensor Core GPUs. 客戶簡介及客戶挑戰 火山引擎機器學習平臺，由字節跳動應用機器學習團隊推出，支撐了抖音、西瓜視頻等產品的AI算法訓練與推理業務。目前機器學習平臺已經正式對外服務，在AI醫療、自動駕駛、AI企業服務等多個行業落地。 AI技術已經成爲醫療健康和生命科學領域發展的重要驅動力，以計算機視覺、自然","text":"案例簡介 隨着AI在醫療健康和生命科學領域應用的不斷增加，GPU算力的需求迅猛增長。火山引擎機器學習平臺在NVIDIA A100 Tensor Core GPU的硬件基礎架構之上，基於NVIDIA Clara 平臺構建面向醫療健康和生命科學的行業方案。通過公有云、專業工具的結合，爲企業提升開發效率。 本案例爲NVIDIA Clara 平臺，NGC（NVIDIA GPU Cloud），NVIDIA A100 Tensor Core GPU。 Case Introduction With the rapid increase of AI applications in healthcare and life science, developers’ need on GPU computation expand at very high speed. With NVIDIA A100 Tensor Core GPUs infrastructure, Volcengine adopt NVIDIA Clara platform to build professional platforms for healthcare and life science industry. Mainly applies to NVIDIA Clara Platform，NGC (NVIDIA GPU Cloud) and NVIDIA A100 Tensor Core GPUs. 客戶簡介及客戶挑戰 火山引擎機器學習平臺，由字節跳動應用機器學習團隊推出，支撐了抖音、西瓜視頻等產品的AI算法訓練與推理業務。目前機器學習平臺已經正式對外服務，在AI醫療、自動駕駛、AI企業服務等多個行業落地。 AI技術已經成爲醫療健康和生命科學領域發展的重要驅動力，以計算機視覺、自然","images":[],"top":1,"highlighted":1,"essential":1,"paper":2,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/688649304","isVote":1,"tweetType":1,"viewCount":0,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"CN","totalScore":0},"isVote":1,"tweetType":1,"viewCount":91,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":9914947859,"gmtCreate":1665181790471,"gmtModify":1676537567554,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"👍","listText":"👍","text":"👍","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":1,"repostSize":0,"link":"https://ttm.financial/post/9914947859","repostId":"1154004620","repostType":4,"repost":{"id":"1154004620","weMediaInfo":{"introduction":"为用户提供金融资讯、行情、数据，旨在帮助投资者理解世界，做投资决策。","home_visible":1,"media_name":"老虎资讯综合","id":"102","head_image":"https://static.tigerbbs.com/8274c5b9d4c2852bfb1c4d6ce16c68ba"},"pubTimestamp":1665155677,"share":"https://ttm.financial/m/news/1154004620?lang=&edition=fundamental","pubTime":"2022-10-07 23:14","market":"us","language":"zh","title":"AMD跌幅扩大至10%，公司下调Q3营收预期","url":"https://stock-news.laohu8.com/highlight/detail?id=1154004620","media":"老虎资讯综合","summary":"10月7日，AMD跌幅扩大至10%，公司下调第三季度营收预期至56亿美元，远低于此前预计的65-69亿美元；其他芯片股跟跌，英伟达跌超5%，英特尔、台积电跌超4%。","content":"<html><head></head><body><p>10月7日，<a href=\"https://laohu8.com/S/AMD\">AMD</a>跌幅扩大至10%，公司下调第三季度营收预期至56亿美元，远低于此前预计的65-69亿美元；其他芯片股跟跌，<a href=\"https://laohu8.com/S/NVDA\">英伟达</a>跌超5%，<a href=\"https://laohu8.com/S/INTC\">英特尔</a>、<a href=\"https://laohu8.com/S/TSM\">台积电</a>跌超4%。</p><p><img src=\"https://static.tigerbbs.com/918102313921e2a336a0c85477e4948a\" tg-width=\"840\" tg-height=\"470\" referrerpolicy=\"no-referrer\"/></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>AMD跌幅扩大至10%，公司下调Q3营收预期</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\">\nAMD跌幅扩大至10%，公司下调Q3营收预期\n</h2>\n\n<h4 class=\"meta\">\n\n\n<a class=\"head\" href=\"https://laohu8.com/wemedia/102\">\n\n\n<div class=\"h-thumb\" style=\"background-image:url(https://static.tigerbbs.com/8274c5b9d4c2852bfb1c4d6ce16c68ba);background-size:cover;\"></div>\n\n<div class=\"h-content\">\n<p class=\"h-name\">老虎资讯综合 </p>\n<p class=\"h-time\">2022-10-07 23:14</p>\n</div>\n\n</a>\n\n\n</h4>\n\n</header>\n<article>\n<html><head></head><body><p>10月7日，<a href=\"https://laohu8.com/S/AMD\">AMD</a>跌幅扩大至10%，公司下调第三季度营收预期至56亿美元，远低于此前预计的65-69亿美元；其他芯片股跟跌，<a href=\"https://laohu8.com/S/NVDA\">英伟达</a>跌超5%，<a href=\"https://laohu8.com/S/INTC\">英特尔</a>、<a href=\"https://laohu8.com/S/TSM\">台积电</a>跌超4%。</p><p><img src=\"https://static.tigerbbs.com/918102313921e2a336a0c85477e4948a\" tg-width=\"840\" tg-height=\"470\" referrerpolicy=\"no-referrer\"/></p></body></html>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/a593d85be38c3aa543ab3056553101ff","relate_stocks":{"BK4534":"瑞士信贷持仓","BK4529":"IDC概念","BK4573":"虚拟现实","GFS":"GLOBALFOUNDRIES Inc.","AMD":"美国超微公司","BK4512":"苹果概念","BK4141":"半导体产品","BK4554":"元宇宙及AR概念","BK4532":"文艺复兴科技持仓","BK4566":"资本集团","BK4575":"芯片概念"},"source_url":"","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1154004620","content_text":"10月7日，AMD跌幅扩大至10%，公司下调第三季度营收预期至56亿美元，远低于此前预计的65-69亿美元；其他芯片股跟跌，英伟达跌超5%，英特尔、台积电跌超4%。","news_type":1},"isVote":1,"tweetType":1,"viewCount":212,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":9044338096,"gmtCreate":1656714255215,"gmtModify":1676535880052,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"<a href=\"https://ttm.financial/S/AMC\">$AMC院线(AMC)$</a>☺","listText":"<a 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href=\"https://ttm.financial/S/AMC\">$AMC院线(AMC)$</a>😊","text":"$AMC院线(AMC)$😊","images":[{"img":"https://community-static.tradeup.com/news/e0680ea2c63ce33ff48aa54a6b7356db","width":"1176","height":"3087"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":3,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/9086735823","isVote":1,"tweetType":1,"viewCount":138,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0},{"id":9086490699,"gmtCreate":1650486707515,"gmtModify":1676534733309,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"<a href=\"https://ttm.financial/S/AMC\">$AMC院线(AMC)$</a>😊","listText":"<a href=\"https://ttm.financial/S/AMC\">$AMC院线(AMC)$</a>😊","text":"$AMC院线(AMC)$😊","images":[{"img":"https://community-static.tradeup.com/news/95813debbe0e3412cc6a88ac3492fabf","width":"1176","height":"3087"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":3,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/9086490699","isVote":1,"tweetType":1,"viewCount":41,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0},{"id":9086088172,"gmtCreate":1650405714100,"gmtModify":1676534712973,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"<a href=\"https://ttm.financial/S/NVDA\">$英伟达(NVDA)$</a>👍","listText":"<a href=\"https://ttm.financial/S/NVDA\">$英伟达(NVDA)$</a>👍","text":"$英伟达(NVDA)$👍","images":[{"img":"https://community-static.tradeup.com/news/e6242f8a4671d7b3dd09a21a182fb552","width":"1176","height":"3087"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/9086088172","isVote":1,"tweetType":1,"viewCount":128,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0},{"id":9089894087,"gmtCreate":1649980166704,"gmtModify":1676534619514,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"<a href=\"https://ttm.financial/S/TSLA\">$特斯拉(TSLA)$</a>👍","listText":"<a href=\"https://ttm.financial/S/TSLA\">$特斯拉(TSLA)$</a>👍","text":"$特斯拉(TSLA)$👍","images":[{"img":"https://community-static.tradeup.com/news/a9e862fa6091881daf31c9d50e6a94df","width":"1176","height":"3087"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":3,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/9089894087","isVote":1,"tweetType":1,"viewCount":54,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0},{"id":9017561775,"gmtCreate":1649801298045,"gmtModify":1676534576205,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"<a href=\"https://ttm.financial/S/NVDA\">$英伟达(NVDA)$</a>😊","listText":"<a href=\"https://ttm.financial/S/NVDA\">$英伟达(NVDA)$</a>😊","text":"$英伟达(NVDA)$😊","images":[{"img":"https://community-static.tradeup.com/news/337e25ed5cde4c01e5ddbe6b63fc54cd","width":"1176","height":"3087"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/9017561775","isVote":1,"tweetType":1,"viewCount":118,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0},{"id":173052309,"gmtCreate":1626589436501,"gmtModify":1703762129006,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"like","listText":"like","text":"like","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":3,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/173052309","repostId":"1139907709","repostType":4,"repost":{"id":"1139907709","pubTimestamp":1626568617,"share":"https://ttm.financial/m/news/1139907709?lang=&edition=fundamental","pubTime":"2021-07-18 08:36","market":"us","language":"en","title":"Wall Street Crime And Punishment: Thomas F. Quinn's Mad, Mad, Mad, Mad World","url":"https://stock-news.laohu8.com/highlight/detail?id=1139907709","media":"Benzinga","summary":"Does crime pay?\nIn August 1988, French authorities arrested an American expatriate named Thomas F. Q","content":"<p><i>Does crime pay?</i></p>\n<p>In August 1988, French authorities arrested an American expatriate named&nbsp;<b>Thomas F. Quinn</b>&nbsp;for orchestrating a global securities scheme that defrauded investors out of $500 million.</p>\n<p>As an unapologetic financial miscreant with a lifelong penchant for fraud, the French escapade represented something of a career peak for Quinn, whose flair of swindling took on an astonishing level of organizing that left no corner of the world untouched.</p>\n<p><b>Illusory Assets For Sale:</b>Thomas Francis Quinn was born in Brooklyn in 1932; his father drove a cement truck and his mother was a housewife who made extra money selling clothing and jewelry from the family’s garage.</p>\n<p>Quinn was an altar boy in his childhood and was the first member of his family to pursue higher education, graduating from St. John’s University Law School and passing the bar in 1962.</p>\n<p>Quinn opted to go into business for himself, starting a brokerage firm in New York called&nbsp;<b>Thomas, Williams &amp; Lee.</b>The main focus of this firm became the promotion of&nbsp;<b>Kent Industries,</b>a company that claimed to own Florida property valued at $2 million.</p>\n<p>There was a slight problem —&nbsp;Kent Industries didn’t own anything in the Sunshine State, and this inconvenient fact helped to introduce Quinn to the U.S. Securities and Exchange Commission (SEC).</p>\n<p>Long story short: Quinn received a lifetime banishment from the SEC in 1966 from doing business with brokers and dealers thanks to what the agency defined as his “flagrant fraudulent practices” related to the Kent Industries assets, which the regulator considered to be “almost completely illusory.”</p>\n<p>The U.S. Department of Justice (DOJ) was a bit slower in dealing with Quinn, but by 1970 he was sent to jail for six months and was later permanently disbarred from practicing law.</p>\n<p><b>A Job With The Mob:</b>Prior to losing his law license, Quinn gained a partnership in a New York-based securities law firm that set off several alarms among federal law enforcement agencies. Indeed, an FBI report from 1983 recalled this firm’s chief focus was being responsible for the “funds of hoodlum-controlled companies.”</p>\n<p>Quinn was on both the FBI’s and SEC’s respective radars in the early 1980s for his role with two companies,<b>Sundance Gold Mining</b>&nbsp;and&nbsp;<b>Aquarius Gold Exploration</b>, that claimed to have discovered gold in Suriname. The companies created a flurry of excitement among investors, but an investigation into their operations found a hitherto undeclared connection with the&nbsp;<b>Genovese crime family.</b></p>\n<p>The SEC filed a civil complaint against Quinn in 1983, charging him with fraudulently manipulating and promoting the companies’ stocks.</p>\n<p>Three years later, he reached a settlement with the regulator by agreeing to permanently stay away from anything related to securities.</p>\n<p>The FBI, despite finding Mafia fingerprints in Quinn’s business affairs, declined to press charges against him.</p>\n<p>Realizing that he wore out his welcome in his home country, Quinn and his common-law wife&nbsp;<b>Rochelle Rothfleisch</b>&nbsp;decided to relocate to France and to up his game to an unprecedented operation.</p>\n<p><b>Boiler Room Follies:</b>The circumstances and details of how Quinn built his swindling masterpiece are a bit fuzzy, but it is believed that the scheme was first hatched in 1984 and was coordinated out of his $6 million villa in the south of France.</p>\n<p>Quinn set up an archipelago of offices in several European countries and in Dubai, Jamaica and the tiny South Pacific island nation of Vanuatu, and he gave them phony names that sounded similar to respectable brokerages.</p>\n<p>Each office was staffed with salesmen who were tasked to sell stocks for 20 U.S. corporations to individual investors around the world. The stocks in question were mostly shell companies trading on the over-the-counter exchanges that Quinn picked up for pennies, but they were resold by Quinn’s salesmen at inflated amounts.</p>\n<p>The investors were culled from mailing lists sold by publishing companies and professional organizations, as well as from respondents to advertisements placed in newsletters focused on the over-the-counter markets.</p>\n<p>Quinn’s henchmen would telephone the investors —&nbsp;nearly all of whom were novices to investing —&nbsp;and do a high-pressure sales spiel that, more often than not, resulted in the separation of the gullible targets from their money.</p>\n<p>Quinn’s team aimed at European, Australian, Middle Eastern and Hong Kong neophyte investors. The only country off-limits from this scheme was the U.S. Quinn was already on the FBI’s radar and the last thing he wanted was to give them cause to pursue him anew.</p>\n<p><b>A Temporary Setback:</b>&nbsp;In 1988, Quinn’s arrest in France&nbsp;saw him charged with securities fraud, forgery of administrative documents and the possession of two fake Greek passports. His detention and the subsequent arrest of 20 of his salesmen created a fascinating dilemma for banking and law enforcement agencies in multiple countries.</p>\n<p>For starters, no one could easily figure out where the majority of Quinn’s $500 million in ill-gotten gains wound up.&nbsp;Transfers were traced through banks in Switzerland, Luxembourg and Gibraltar, as well as the beleaguered&nbsp;<b>Bank of Credit and Commerce International</b>&nbsp;in Tampa, Florida, which gained national attention as a favored depository for those involved in drug money laundering. But where the money eventually landed was anyone’s guess, and Quinn’s talent for adopting aliases to cover his business tracks confounded investigators.</p>\n<p>Also, it was unclear regarding how many people were swindled. A pair of class-action lawsuits brought out a total of 500 people trying to regain their money, but some observers of this case speculated the number could have been higher — some investors might have seen Quinn’s scam as a means of evading local taxes and foreign currency exchanges and would then have to answer to their authorities if this chicanery came to light.</p>\n<p>The SEC got into the picture because the stocks being sold in the scheme were all U.S. companies. The agency hosted a meeting in Washington D.C.&nbsp;with law enforcement officers and prosecutors from eight European countries and Australia, with the hopes of sorting out the mess. But since no Americans were defrauded in this elaborate charade, Quinn did not face criminal charges in his own country, although the SEC temporarily froze his U.S. assets.</p>\n<p>In France, Quinn was initially released after agreeing to reimburse his French victims but was arrested again when the Swiss government demanded his extradition.</p>\n<p>He came to trial in 1991 and was only sentenced to four years in prison,&nbsp;but his sentence was reduced to include time served and he was extradited to Switzerland.</p>\n<p>His Alpine detention was brief and by the mid-1990s he returned to the U.S. and rented a luxury home in Greenwich, Connecticut, a swanky suburb of New York City.</p>\n<p><b>An Eventual Stumble:</b>One of Quinn’s neighbors in Greenwich was<b>Martin Frankel,</b>a financier with his own addiction to swindling.</p>\n<p>In 1999, the Wall Street Journal used anonymous “people familiar with the matter” to claim Quinn assisted Frankel in his efforts to raise money for a controlled investment fund designed to buy insurance companies —&nbsp;but this turned out to be an embezzlement scam that resulted in Frankel fleeing the U.S. to Germany on a phony passport.</p>\n<p>Frankel was eventually extradited and spent nearly two decades in prison, but Quinn was never charged for being a partner in Frankel’s shenanigans.</p>\n<p>For most of the 1990s and the 2000s, Quinn kept a very low public profile, although law enforcement tracked his travels to such far-flung places as the Maldives and the United Arab Emirates.</p>\n<p>In 2004, he made a rare appearance at the Irish Derby as the co-owner of the winning thoroughbred Grey Swallow. Photographs of Quinn with the winning racehorse marked the only time that he was ever photographed in a public gathering. (Copyright restrictions prevent us from reprinting the photograph here, butthis linkon the RTE website shows Quinn, standing second from right, at the conclusion of the championship race.)</p>\n<p>In November 2009, Quinn’s luck finally ran out. On a trip back from Ireland to New York’s JFK International Airport, he was arrested for his role within a ring of embezzlers that sought to defraud a pair of British telecommunications companies out of more than $60 million. The scheme had the global hallmarks of Quinn’s earlier criminal triumph, with funds being disbursed to seven countries across four continents.</p>\n<p>Quinn was immediately jailed upon his arrest and was denied bail because it was feared he would attempt to flee the country. He eventually pleaded guilty to a single count of wire fraud and, despite exhortations to avoid prison due to health problems, he was sentenced in March 2013 to 84 months in prison. He was released in May 2016.</p>\n<p>What became of Quinn since his release is unknown. No obituary for him has been published, and he would be 89 years old if he is still alive.</p>\n<p>One information-tracking website listed him residing at a Brooklyn address, but the website also listed an accompanying telephone number that is not in service. Any readers who may have information on Quinn’s whereabouts should contact us and we will offer an update on his story.</p>\n<p>Quinn rarely spoke to anyone about his criminal activities.&nbsp;During an investigative session after his final arrest, he reportedly would only answer questions through a series of eyelid blinks. When a reporter sought to interview him in 1995, he demanded his privacy.</p>\n<p>\"Just forget me,\" Quinn said. \"I've got a lot of trouble and a lot of personal grief. I'm just trying to get on with my life. I'm not in the securities business and never will be again.\"</p>","source":"lsy1606299360108","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>Wall Street Crime And Punishment: Thomas F. Quinn's Mad, Mad, Mad, Mad World</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\">\nWall Street Crime And Punishment: Thomas F. Quinn's Mad, Mad, Mad, Mad World\n</h2>\n\n<h4 class=\"meta\">\n\n\n2021-07-18 08:36 GMT+8&nbsp;&nbsp;&nbsp;<a href=https://www.benzinga.com/government/21/07/21990476/wall-street-crime-and-punishment-thomas-f-quinns-mad-mad-mad-mad-world><strong>Benzinga</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>Does crime pay?\nIn August 1988, French authorities arrested an American expatriate named Thomas F. Quinn for orchestrating a global securities scheme that defrauded investors out of $500 million.\nAs ...</p>\n\n<a href=\"https://www.benzinga.com/government/21/07/21990476/wall-street-crime-and-punishment-thomas-f-quinns-mad-mad-mad-mad-world\">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://www.benzinga.com/government/21/07/21990476/wall-street-crime-and-punishment-thomas-f-quinns-mad-mad-mad-mad-world","is_english":true,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1139907709","content_text":"Does crime pay?\nIn August 1988, French authorities arrested an American expatriate named Thomas F. Quinn for orchestrating a global securities scheme that defrauded investors out of $500 million.\nAs an unapologetic financial miscreant with a lifelong penchant for fraud, the French escapade represented something of a career peak for Quinn, whose flair of swindling took on an astonishing level of organizing that left no corner of the world untouched.\nIllusory Assets For Sale:Thomas Francis Quinn was born in Brooklyn in 1932; his father drove a cement truck and his mother was a housewife who made extra money selling clothing and jewelry from the family’s garage.\nQuinn was an altar boy in his childhood and was the first member of his family to pursue higher education, graduating from St. John’s University Law School and passing the bar in 1962.\nQuinn opted to go into business for himself, starting a brokerage firm in New York called Thomas, Williams & Lee.The main focus of this firm became the promotion of Kent Industries,a company that claimed to own Florida property valued at $2 million.\nThere was a slight problem — Kent Industries didn’t own anything in the Sunshine State, and this inconvenient fact helped to introduce Quinn to the U.S. Securities and Exchange Commission (SEC).\nLong story short: Quinn received a lifetime banishment from the SEC in 1966 from doing business with brokers and dealers thanks to what the agency defined as his “flagrant fraudulent practices” related to the Kent Industries assets, which the regulator considered to be “almost completely illusory.”\nThe U.S. Department of Justice (DOJ) was a bit slower in dealing with Quinn, but by 1970 he was sent to jail for six months and was later permanently disbarred from practicing law.\nA Job With The Mob:Prior to losing his law license, Quinn gained a partnership in a New York-based securities law firm that set off several alarms among federal law enforcement agencies. Indeed, an FBI report from 1983 recalled this firm’s chief focus was being responsible for the “funds of hoodlum-controlled companies.”\nQuinn was on both the FBI’s and SEC’s respective radars in the early 1980s for his role with two companies,Sundance Gold Mining and Aquarius Gold Exploration, that claimed to have discovered gold in Suriname. The companies created a flurry of excitement among investors, but an investigation into their operations found a hitherto undeclared connection with the Genovese crime family.\nThe SEC filed a civil complaint against Quinn in 1983, charging him with fraudulently manipulating and promoting the companies’ stocks.\nThree years later, he reached a settlement with the regulator by agreeing to permanently stay away from anything related to securities.\nThe FBI, despite finding Mafia fingerprints in Quinn’s business affairs, declined to press charges against him.\nRealizing that he wore out his welcome in his home country, Quinn and his common-law wife Rochelle Rothfleisch decided to relocate to France and to up his game to an unprecedented operation.\nBoiler Room Follies:The circumstances and details of how Quinn built his swindling masterpiece are a bit fuzzy, but it is believed that the scheme was first hatched in 1984 and was coordinated out of his $6 million villa in the south of France.\nQuinn set up an archipelago of offices in several European countries and in Dubai, Jamaica and the tiny South Pacific island nation of Vanuatu, and he gave them phony names that sounded similar to respectable brokerages.\nEach office was staffed with salesmen who were tasked to sell stocks for 20 U.S. corporations to individual investors around the world. The stocks in question were mostly shell companies trading on the over-the-counter exchanges that Quinn picked up for pennies, but they were resold by Quinn’s salesmen at inflated amounts.\nThe investors were culled from mailing lists sold by publishing companies and professional organizations, as well as from respondents to advertisements placed in newsletters focused on the over-the-counter markets.\nQuinn’s henchmen would telephone the investors — nearly all of whom were novices to investing — and do a high-pressure sales spiel that, more often than not, resulted in the separation of the gullible targets from their money.\nQuinn’s team aimed at European, Australian, Middle Eastern and Hong Kong neophyte investors. The only country off-limits from this scheme was the U.S. Quinn was already on the FBI’s radar and the last thing he wanted was to give them cause to pursue him anew.\nA Temporary Setback: In 1988, Quinn’s arrest in France saw him charged with securities fraud, forgery of administrative documents and the possession of two fake Greek passports. His detention and the subsequent arrest of 20 of his salesmen created a fascinating dilemma for banking and law enforcement agencies in multiple countries.\nFor starters, no one could easily figure out where the majority of Quinn’s $500 million in ill-gotten gains wound up. Transfers were traced through banks in Switzerland, Luxembourg and Gibraltar, as well as the beleaguered Bank of Credit and Commerce International in Tampa, Florida, which gained national attention as a favored depository for those involved in drug money laundering. But where the money eventually landed was anyone’s guess, and Quinn’s talent for adopting aliases to cover his business tracks confounded investigators.\nAlso, it was unclear regarding how many people were swindled. A pair of class-action lawsuits brought out a total of 500 people trying to regain their money, but some observers of this case speculated the number could have been higher — some investors might have seen Quinn’s scam as a means of evading local taxes and foreign currency exchanges and would then have to answer to their authorities if this chicanery came to light.\nThe SEC got into the picture because the stocks being sold in the scheme were all U.S. companies. The agency hosted a meeting in Washington D.C. with law enforcement officers and prosecutors from eight European countries and Australia, with the hopes of sorting out the mess. But since no Americans were defrauded in this elaborate charade, Quinn did not face criminal charges in his own country, although the SEC temporarily froze his U.S. assets.\nIn France, Quinn was initially released after agreeing to reimburse his French victims but was arrested again when the Swiss government demanded his extradition.\nHe came to trial in 1991 and was only sentenced to four years in prison, but his sentence was reduced to include time served and he was extradited to Switzerland.\nHis Alpine detention was brief and by the mid-1990s he returned to the U.S. and rented a luxury home in Greenwich, Connecticut, a swanky suburb of New York City.\nAn Eventual Stumble:One of Quinn’s neighbors in Greenwich wasMartin Frankel,a financier with his own addiction to swindling.\nIn 1999, the Wall Street Journal used anonymous “people familiar with the matter” to claim Quinn assisted Frankel in his efforts to raise money for a controlled investment fund designed to buy insurance companies — but this turned out to be an embezzlement scam that resulted in Frankel fleeing the U.S. to Germany on a phony passport.\nFrankel was eventually extradited and spent nearly two decades in prison, but Quinn was never charged for being a partner in Frankel’s shenanigans.\nFor most of the 1990s and the 2000s, Quinn kept a very low public profile, although law enforcement tracked his travels to such far-flung places as the Maldives and the United Arab Emirates.\nIn 2004, he made a rare appearance at the Irish Derby as the co-owner of the winning thoroughbred Grey Swallow. Photographs of Quinn with the winning racehorse marked the only time that he was ever photographed in a public gathering. (Copyright restrictions prevent us from reprinting the photograph here, butthis linkon the RTE website shows Quinn, standing second from right, at the conclusion of the championship race.)\nIn November 2009, Quinn’s luck finally ran out. On a trip back from Ireland to New York’s JFK International Airport, he was arrested for his role within a ring of embezzlers that sought to defraud a pair of British telecommunications companies out of more than $60 million. The scheme had the global hallmarks of Quinn’s earlier criminal triumph, with funds being disbursed to seven countries across four continents.\nQuinn was immediately jailed upon his arrest and was denied bail because it was feared he would attempt to flee the country. He eventually pleaded guilty to a single count of wire fraud and, despite exhortations to avoid prison due to health problems, he was sentenced in March 2013 to 84 months in prison. He was released in May 2016.\nWhat became of Quinn since his release is unknown. No obituary for him has been published, and he would be 89 years old if he is still alive.\nOne information-tracking website listed him residing at a Brooklyn address, but the website also listed an accompanying telephone number that is not in service. Any readers who may have information on Quinn’s whereabouts should contact us and we will offer an update on his story.\nQuinn rarely spoke to anyone about his criminal activities. During an investigative session after his final arrest, he reportedly would only answer questions through a series of eyelid blinks. When a reporter sought to interview him in 1995, he demanded his privacy.\n\"Just forget me,\" Quinn said. \"I've got a lot of trouble and a lot of personal grief. I'm just trying to get on with my life. I'm not in the securities business and never will be again.\"","news_type":1},"isVote":1,"tweetType":1,"viewCount":84,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":238342703579144,"gmtCreate":1699224673880,"gmtModify":1699224676504,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"<a href=\"https://ttm.financial/S/VIST\">$Vista Oil &amp; Gas, S.A.B. de C.V.(VIST)$ &nbsp;</a>","listText":"<a href=\"https://ttm.financial/S/VIST\">$Vista Oil &amp; Gas, S.A.B. de C.V.(VIST)$ &nbsp;</a>","text":"$Vista Oil & Gas, S.A.B. de C.V.(VIST)$","images":[{"img":"https://community-static.tradeup.com/news/9eb5ef44ae936e9f4398d6ba6c0001d1","width":"882","height":"1608"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":2,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/238342703579144","isVote":1,"tweetType":1,"viewCount":372,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0},{"id":237992248033480,"gmtCreate":1699139272634,"gmtModify":1699139275569,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"<a href=\"https://ttm.financial/S/Y92.SI\">$泰国酿酒(Y92.SI)$ &nbsp;</a>","listText":"<a href=\"https://ttm.financial/S/Y92.SI\">$泰国酿酒(Y92.SI)$ &nbsp;</a>","text":"$泰国酿酒(Y92.SI)$","images":[{"img":"https://community-static.tradeup.com/news/0d6d9ccb9931d836440ae2f968c46e4b","width":"882","height":"1608"}],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":2,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/237992248033480","isVote":1,"tweetType":1,"viewCount":335,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":1,"langContent":"EN","totalScore":0},{"id":9929512495,"gmtCreate":1670700133017,"gmtModify":1676538418899,"author":{"id":"4089446698597000","authorId":"4089446698597000","name":"alvin240576","avatar":"https://static.tigerbbs.com/f0bdcd8cba31f307885b40ed001906e1","crmLevel":2,"crmLevelSwitch":0,"followedFlag":false,"idStr":"4089446698597000","authorIdStr":"4089446698597000"},"themes":[],"htmlText":"good","listText":"good","text":"good","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":2,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/9929512495","isVote":1,"tweetType":1,"viewCount":265,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0}],"lives":[]}