Dojo AI训练计算机

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整理:每日美股市场要闻速递(6月6日 周五)
news flash· 2025-06-06 13:06
金十数据整理:每日美股市场要闻速递(6月6日 周五) 重要新闻 1. 美国5月失业率录得4.2%,符合市场预期。 1. 沃尔玛百货(WMT.N)加码无人机配送,力求加快订单送达速度。 11. 欧洲药品监管机构称,服用诺和诺德(NVO.US)的Ozempic和Wegovy等减肥药的患者存在视力下降的 风险。 12. 市场消息:高盛分析师下调了特斯拉(TSLA.O)的交付预测,大幅下调了盈利预期,并降低了对该品 牌在主要市场的增长势头的预期。 2. 美国5月季调后非农就业人口 13.9万人,预期13万人,前值由17.7万人修正为14.7万人。 3. 综合媒体报道,特朗普表示没有兴趣与马斯克通话,马斯克可能与美国总统特朗普的幕僚进行交谈, 以缓解双方的纷争。 个股新闻 13. 稳定币第一股Circle(CRCL.O)上市次日盘前续涨超14%,昨日收涨168.48%。 2. 高盛(GS.N)下调特斯拉(TSLA.O)交付预期,大幅下调了盈利预期,目标价降至285美元。 3. Uber(UBER.N)考虑用稳定币降低跨境货币成本,已进入研究阶段。 4. 博通(AVGO.O)预计2025财年AI芯片销售的增长势头将延续至 ...
特斯拉下一代AI芯片,将亮相
半导体芯闻· 2025-06-06 10:20
Group 1 - The core viewpoint of the article highlights the progress of Tesla's Dojo AI training computer and the upcoming launch of the next-generation AI chip, Dojo 2, later this year. It emphasizes that significant technological advancements require multiple iterations, with Dojo 3 expected to be even better than its predecessor [1] - Tesla AI's latest Dojo technology report indicates that the Dojo supercomputer is facing issues related to manufacturing defects and aging, which lead to silent data corruption (SDC). Unlike traditional system failures, these defects do not manifest immediately but compromise data integrity during training [1] - A defective node can result in erroneous outcomes from weeks of AI model training or significantly slow down convergence speed. More critically, these issues are nearly undetectable after model training is completed, potentially leading companies to deploy AI systems trained on corrupted data without their knowledge [1] Group 2 - The Dojo supercomputer, designed by Tesla, serves as a training ground for artificial intelligence, particularly for Full Self-Driving (FSD) applications. The name "Dojo" pays homage to martial arts training halls [1] - The supercomputer consists of thousands of small computers known as nodes, each equipped with its own CPU (Central Processing Unit) for overall management and GPU (Graphics Processing Unit) for handling complex tasks, such as dividing tasks into multiple parts for simultaneous processing [1]