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2倍做多TSLA ETF-Direxion(TSLL)
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popo
·
刚刚
$2倍做多TSLA ETF-Direxion(TSLL)$
这两天不涨个10%?
$2倍做多TSLA ETF-Direxion(TSLL)$ 这两天不涨个10%?
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春风不解夏季情
·
19:59
看涨英伟达,的确市盈率不高,和特斯拉比非常的,所以我坚持看涨。期待达子上300
看涨英伟达,的确市盈率不高,和特斯拉比非常的,所以我坚持看涨。期待达子上300
# 英伟达股价两连跌!谨慎观望?
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春天风云
·
19:57
看涨英伟达,的确市盈率不高,和特斯拉比非常的,所以我坚持看涨。期待达子上300
看涨英伟达,的确市盈率不高,和特斯拉比非常的,所以我坚持看涨。期待达子上300
# 英伟达股价两连跌!谨慎观望?
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勇敢_小虎
·
19:25
看涨英伟达,的确市盈率不高,和特斯拉比非常的,所以我坚持看涨。期待达子上300
看涨英伟达,的确市盈率不高,和特斯拉比非常的,所以我坚持看涨。期待达子上300
# 英伟达股价两连跌!谨慎观望?
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Mcrowe
·
01-06 19:58
英伟达没有意义的空谈是没用的,ai再好也需要实践过的数据,而特斯拉无论是ai还是实践都很充足了,所以我站特斯拉
英伟达没有意义的空谈是没用的,ai再好也需要实践过的数据,而特斯拉无论是ai还是实践都很充足了,所以我站特斯拉
# 英伟达股价两连跌!谨慎观望?
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ZebulonToynbee:
特斯拉确实牛,实践数据硬核!
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春天风云
·
01-06 20:47
看好特斯拉,特斯拉的自动驾驶到2026年是关键一年,现在美国应该是开始上线了,看别人的试驾效果不错。值得投入特斯拉。建议增持。
看好特斯拉,特斯拉的自动驾驶到2026年是关键一年,现在美国应该是开始上线了,看别人的试驾效果不错。值得投入特斯拉。建议增持。
# 英伟达股价两连跌!谨慎观望?
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windy00:
特斯拉自动驾驶真猛,增持稳赚!
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梦想快实现
·
01-06 20:44
相当于英伟达进来成为鲶鱼效应,而不一定能做到秒杀,毕竟经验和自动驾驶的生态供应链还是特斯拉的强项,但会加速特斯拉做得更好
相当于英伟达进来成为鲶鱼效应,而不一定能做到秒杀,毕竟经验和自动驾驶的生态供应链还是特斯拉的强项,但会加速特斯拉做得更好
# 英伟达股价两连跌!谨慎观望?
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PatrickPatterson:
鲶鱼效应真能激发特斯拉潜力!
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大碗888
·
01-06 20:42
英伟达没有意义的空谈是没用的,ai再好也需要实践过的数据,而特斯拉无论是ai还是实践都很充足了,所以我站特斯拉
英伟达没有意义的空谈是没用的,ai再好也需要实践过的数据,而特斯拉无论是ai还是实践都很充足了,所以我站特斯拉
# 英伟达股价两连跌!谨慎观望?
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beginnerRio:
支持特斯拉,落地实践真靠谱!
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春风不解夏季情
·
01-06 20:27
更看好特斯拉,因为特斯拉的自动驾驶系统与车是紧密联系的,英伟达的自动驾驶系统缺乏车上的时间,因此需要走很长一段路
更看好特斯拉,因为特斯拉的自动驾驶系统与车是紧密联系的,英伟达的自动驾驶系统缺乏车上的时间,因此需要走很长一段路
# 英伟达股价两连跌!谨慎观望?
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MabelReed:
特斯拉自动驾驶真香,整合力超强!
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小小虎AAA
·
01-06 20:22
我更支持特斯拉,因为特斯拉是耕耘自动驾驶很久了,有充分的实践经验
我更支持特斯拉,因为特斯拉是耕耘自动驾驶很久了,有充分的实践经验
# 英伟达股价两连跌!谨慎观望?
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a9032:
特斯拉自动驾驶积累深,稳拿!
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追梦999
·
01-06 20:14
看好特斯拉,特斯拉的自动驾驶到2026年是关键一年,现在美国应该是开始上线了,看别人的试驾效果不错。值得投入特斯拉。建议增持。
看好特斯拉,特斯拉的自动驾驶到2026年是关键一年,现在美国应该是开始上线了,看别人的试驾效果不错。值得投入特斯拉。建议增持。
# 英伟达股价两连跌!谨慎观望?
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MMMia:
自动驾驶真香,特斯拉冲一波!
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追梦999
·
01-06 20:13
更看好特斯拉,因为英伟达不造车它的系统需要在车上反复的时间训练检验才可能让人信服
更看好特斯拉,因为英伟达不造车它的系统需要在车上反复的时间训练检验才可能让人信服
# 无视地缘冲突!.SPX & BTC,你的投资方向是?
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MabelReed:
同意,自研系统才是王道!
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苍穹之剑888
·
01-06 20:11
更看好特斯拉,因为特斯拉他的自动驾驶系统可以在车 充分的去实践去修正
更看好特斯拉,因为特斯拉他的自动驾驶系统可以在车 充分的去实践去修正
# 英伟达股价两连跌!谨慎观望?
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LucyRosa:
特斯拉自动驾驶太强了,我车上试过超准!
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明日阳光888
·
01-06 20:07
更看好特斯拉,因为特斯拉的自动驾驶系统与车是紧密联系的,英伟达的自动驾驶系统缺乏车上的时间,因此需要走很长一段路
更看好特斯拉,因为特斯拉的自动驾驶系统与车是紧密联系的,英伟达的自动驾驶系统缺乏车上的时间,因此需要走很长一段路
# 英伟达股价两连跌!谨慎观望?
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SteveWatson:
特斯拉软硬一体优势明显,英伟达还得拼。
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勇敢_小虎
·
01-06 16:26
看好特斯拉,特斯拉的自动驾驶到2026年是关键一年,现在美国应该是开始上线了,看别人的试驾效果不错。值得投入特斯拉。建议增持。
看好特斯拉,特斯拉的自动驾驶到2026年是关键一年,现在美国应该是开始上线了,看别人的试驾效果不错。值得投入特斯拉。建议增持。
# 英伟达股价两连跌!谨慎观望?
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AbnerKeppel:
自动驾驶牛啊,我也加仓了!
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花香满楼
·
01-06 16:06
英伟达进圈,搅动自动驾驶行业,也是好事。特斯拉有竞争才有动力做的更好
英伟达进圈,搅动自动驾驶行业,也是好事。特斯拉有竞争才有动力做的更好
# 英伟达股价两连跌!谨慎观望?
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GriseldaBrown:
竞争是好事,特斯拉更拼了!
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awyer
·
01-06 17:15
英伟达的开源模型,等于是帮特斯拉的封闭模型补足了短板,马斯克不知道多高兴。监管部门最怕垄断,现在有了一个开源模型来了,非特斯拉车企有机会参与进来,避免了特斯拉独大;皮夹克又可以多卖芯片;特斯拉用的是FSD+英伟达开源版保持绝对领先。根本就是皮夹克和马斯克商量好的。
英伟达做了个FSD?马斯克淡定回应:我不会为此失眠
英伟达CES发布开源自动驾驶模型Alpamayo,号称“物理AI的ChatGPT时刻”,将随奔驰CLA一季度上路。面对这一能“思考推理”的强劲对手,马斯克回应称解决长尾问题才是关键,并直言:“我才不会因为这个失眠,真心希望他们能成功。”
英伟达做了个FSD?马斯克淡定回应:我不会为此失眠
英伟达的开源模型,等于是帮特斯拉的封闭模型补足了短板,马斯克不知道多高兴。监管部门最怕垄断,现在有了一个开源模型来了,非特斯拉车企有机会参与进来,避免了特...
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特斯拉
·
01-06 16:04
这些年,特斯拉为车友免费升级了多少实用功能?🧐
2022-2025年累计推送了 58次OTA远程升级,带来100+项实用功能更新 娱乐🎮出行🚘控车📲统统搞定 一次购买,更新不断,进化不停🧬 新年开新车,不花钱也能体验“新车感” 安全智能又好玩,这就是特斯拉车主们的快乐[爱你]
这些年,特斯拉为车友免费升级了多少实用功能?🧐
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顺势而为把握时机
·
01-06 04:39
特斯拉最近不行
截至2026年1月5日,特斯拉(TSLA)收于438.07美元,已七连跌,短期偏空,中期关键看支撑与量能变化。以下是核心结论与实操位。 一、走势速览 - 驱动:**Q4交付同比-15.6%、全年-8.6%**不及预期,政策红利消退、竞争加剧、车型迭代慢,情绪偏弱 。 - 技术:失守50日均线(445美元),RSI约45.89(中性),MACD空头,短期反弹动能不足。 - 结构:从12月近500美元回落,处于高位回调,关注430-440与400-410支撑带。 二、支撑位(由近及远) - 第一支撑:430-435美元,近期成交密集区,1月2日低点435.30美元,破位下探第二支撑。 - 第二支撑:418-424美元,周线关键位+100日均线,强支撑,失守或加速至400美元。 - 第三支撑:400-406美元,心理关口+前期平台,若放量跌破,中期转弱概率上升。 - 强支撑:360-361美元(200日均线),中期多空分水岭,接近或触及易引发技术性反弹。 三、压力位(由近及远) - 第一压力:444-449美元,50日均线+近期平台,收复转中性,受阻延续弱势。 - 第二压力:463-464美元,21日均线+前期震荡上沿,突破则缓解七连跌情绪。 - 第三压力:475-490美元,12月多次冲击未果,机构兑现区,需放量突破才有望再攻500美元。 - 强压力:500美元,心理+历史高位,年内多次承压,突破需基本面与资金共振。 四、操作建议 - 短线:以444美元为多空线,站上看463-475,止损430;跌破430则看418-424,止损406下方。 - 中线:等400-420企稳+放量止跌再布局,防守200日均线;若464放量突破,可轻仓追多,目标490-500。 - 风险:交付疲软、政策退坡、竞争加剧、马斯克舆情,控制仓位,期权交易者可结合波动率做策略 。 五、总结 短期偏空,先看
特斯拉最近不行
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火火兔爸
·
01-01
单就特斯拉的保有数量一旦新的fsd订阅量大幅上升都可以很好的提升利润
马斯克10年梦成真!特斯拉全球首次自动驾驶横穿美国,人类0次接管
刚刚,特斯拉FSD,完成全球首个完全自动驾驶的横穿美国。从美国西海岸开到东海岸,2天20小时,人类0次接管。特斯拉官方账号,表扬了这次壮举。全球首次人类零接管下面这份数据,让人难以抑制心头的震撼。从2016年,特斯拉的FSD系统就开始宣传「零干预横贯美国」的目标。然而David Moss晒出的仪表盘显示,FSD V14千真万确完成了100%的完全自动驾驶。尽管特斯拉坚信端到端神经网络技术,但这绝非自动驾驶领域的共识方案。
马斯克10年梦成真!特斯拉全球首次自动驾驶横穿美国,人类0次接管
单就特斯拉的保有数量一旦新的fsd订阅量大幅上升都可以很好的提升利润
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VIX模式:
明年是不是着重做多特斯拉
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src=\"https://community-static.tradeup.com/news/962b7db4bee1027917e211e73b58ad87\" tg-width=\"1024\" tg-height=\"1013\"/></p><h2 id=\"id_3075483512\">英伟达的"推理式"自动驾驶</h2><p><strong>英伟达将Alpamayo称为"物理AI的ChatGPT时刻"。</strong>这一开源AI模型家族旨在解决自动驾驶的"长尾问题",即那些导致自动驾驶系统脱离或失败的罕见边缘案例。</p><p>旗舰产品Alpamayo 1是一个拥有100亿参数的视觉-语言-行动(VLA)模型。与传统自动驾驶系统仅检测物体和规划路径不同,Alpamayo采用"链式推理"方式。它处理视频输入并生成行驶轨迹,但更关键的是,它还会输出决策背后的逻辑。</p><p>黄仁勋表示:<strong>“这不仅仅是一个驾驶模型,而是一个能解释自己思考过程的模型。”</strong>展会上黄仁勋播放了一段演示视频,Alpamayo不仅能驾驶汽车,还能用自然语言解释自己的决策逻辑,例如“前方车辆刹车灯亮起,它可能减速,所以我应该保持距离”。</p><h2 id=\"id_1957901506\">开源策略对抗特斯拉封闭系统</h2><p>英伟达正通过全面的开源策略切入自动驾驶领域,其最新发布的Alpamayo 1模型权重已在Hugging Face平台开放获取,同步推出的还包括端到端仿真框架AlpaSim以及涵盖1700小时复杂驾驶场景的物理AI开放数据集。</p><p><strong>此举标志着英伟达正以“自动驾驶领域的安卓系统”为定位,构建开放生态,与特斯拉完全封闭的FSD系统形成差异化竞争路径</strong>。英伟达同时宣布,该项技术将自今年第一季度起搭载于梅赛德斯-奔驰CLA车型上,迈出商业化落地的重要一步。</p><h2 id=\"id_2999805665\">马斯克的"长尾问题"论</h2><p>马斯克的回应直指自动驾驶行业的核心瓶颈:模型性能的“长尾困境”。他指出,实现99%场景的高准确率相对可行,但攻克剩余1%的罕见却至关重要的“边缘案例”,才是真正决定技术能否安全落地的关键。</p><p>即便英伟达发布了推理能力更强的开源模型,在应对现实道路的极端复杂性和不确定性时,仍难以绕过特斯拉通过大规模部署所建立的数据与工程壁垒。</p><p>目前,特斯拉FSD系统已在全球数百万辆车上持续运行,积累了涵盖海量场景、尤其是“长尾问题”的真实道路数据与闭环优化经验,这正是其在迭代效率和场景覆盖深度上的结构性优势。</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>英伟达做了个FSD?马斯克淡定回应:我不会为此失眠</title>\n<style 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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英伟达做了个FSD?马斯克淡定回应:我不会为此失眠\n</h2>\n\n<h4 class=\"meta\">\n\n\n2026-01-06 15:50 北京时间 <a href=https://wallstreetcn.com/articles/3762641><strong>华尔街见闻</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>英伟达在CES 2026展会上推出名为Alpamayo的开源自动驾驶AI模型,CEO黄仁勋称其为\"世界上首款能思考、能推理的自动驾驶汽车AI\",直接挑战特斯拉的FSD系统。1月6日,电动汽车分析师Sawyer Merritt在X平台发帖称,英伟达宣布将于今年晚些时候在美国道路上推出Alpamayo。马斯克对此回应称:\"好吧,这正是特斯拉在做的。他们会发现,达到99%很容易,但要解决分布的长尾问题却...</p>\n\n<a href=\"https://wallstreetcn.com/articles/3762641\">网页链接</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/f51e0887617e5ccdb1f56ab9d6b7e088","relate_stocks":{"SG9999014559.SGD":"United Income Focus Trust Dis SGD","IE0005OL40V9.USD":"JANUS HENDERSON BALANCED \"A6M\" (USD) INC","NVDY":"NVDA期权收益策略ETF-YieldMax","BK4588":"碎股","BK4550":"红杉资本持仓","LU2236285917.USD":"ALLIANZ GLOBAL INCOME \"AMG\" (USD) INC","NVDA":"英伟达","LU1496350502.SGD":"FRANKLIN DIVERSIFIED DYNAMIC \"A\" (SGDHDG) ACC","LU0724617625.USD":"BGF GLOBAL ALLOCATION \"A4\" (USD) INC","SG9999014567.USD":"UOB UNITED INCOME FOCUS TRUST FUND (USD) ACC","BK4551":"寇图资本持仓","BK4598":"佩洛西持仓","LU0210533765.USD":"JPM GLOBAL GROWTH \"A\" (USD) ACC","LU0788109477.HKD":"BGF GLOBAL ALLOCATION \"A2\" (HKDHGD) ACC","LU1674673691.USD":"HSBC GIF GLOBAL LOWER CARBON EQUITY \"AD\" (USD) INC","LU0316494557.USD":"FRANKLIN GLOBAL FUNDAMENTAL STRATEGIES \"A\" ACC","LU2357125470.USD":"BNP PARIBAS 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ETF-T-Rex"},"source_url":"https://wallstreetcn.com/articles/3762641","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"2601640188","content_text":"英伟达在CES 2026展会上推出名为Alpamayo的开源自动驾驶AI模型,CEO黄仁勋称其为\"世界上首款能思考、能推理的自动驾驶汽车AI\",直接挑战特斯拉的FSD系统。1月6日,电动汽车分析师Sawyer Merritt在X平台发帖称,英伟达宣布将于今年晚些时候在美国道路上推出Alpamayo。马斯克对此回应称:\"好吧,这正是特斯拉在做的。他们会发现,达到99%很容易,但要解决分布的长尾问题却非常困难。\"当有网友表示担心Alpamayo成为FSD的首个真正竞争对手,并指出英伟达可以在没有任何车队的情况下达到接近99%的水平,证明大规模车队数据已不再重要时,马斯克再次回应:\"我才不会因为这个失眠呢。我真心希望他们能成功。\"英伟达的\"推理式\"自动驾驶英伟达将Alpamayo称为\"物理AI的ChatGPT时刻\"。这一开源AI模型家族旨在解决自动驾驶的\"长尾问题\",即那些导致自动驾驶系统脱离或失败的罕见边缘案例。旗舰产品Alpamayo 1是一个拥有100亿参数的视觉-语言-行动(VLA)模型。与传统自动驾驶系统仅检测物体和规划路径不同,Alpamayo采用\"链式推理\"方式。它处理视频输入并生成行驶轨迹,但更关键的是,它还会输出决策背后的逻辑。黄仁勋表示:“这不仅仅是一个驾驶模型,而是一个能解释自己思考过程的模型。”展会上黄仁勋播放了一段演示视频,Alpamayo不仅能驾驶汽车,还能用自然语言解释自己的决策逻辑,例如“前方车辆刹车灯亮起,它可能减速,所以我应该保持距离”。开源策略对抗特斯拉封闭系统英伟达正通过全面的开源策略切入自动驾驶领域,其最新发布的Alpamayo 1模型权重已在Hugging Face平台开放获取,同步推出的还包括端到端仿真框架AlpaSim以及涵盖1700小时复杂驾驶场景的物理AI开放数据集。此举标志着英伟达正以“自动驾驶领域的安卓系统”为定位,构建开放生态,与特斯拉完全封闭的FSD系统形成差异化竞争路径。英伟达同时宣布,该项技术将自今年第一季度起搭载于梅赛德斯-奔驰CLA车型上,迈出商业化落地的重要一步。马斯克的\"长尾问题\"论马斯克的回应直指自动驾驶行业的核心瓶颈:模型性能的“长尾困境”。他指出,实现99%场景的高准确率相对可行,但攻克剩余1%的罕见却至关重要的“边缘案例”,才是真正决定技术能否安全落地的关键。即便英伟达发布了推理能力更强的开源模型,在应对现实道路的极端复杂性和不确定性时,仍难以绕过特斯拉通过大规模部署所建立的数据与工程壁垒。目前,特斯拉FSD系统已在全球数百万辆车上持续运行,积累了涵盖海量场景、尤其是“长尾问题”的真实道路数据与闭环优化经验,这正是其在迭代效率和场景覆盖深度上的结构性优势。","news_type":1,"symbols_score_info":{"TSLA":1.93,"NVDU":0.6,"NVDL":0.6,"NVDD":0.6,"NVD":0.6,"NVDY":0.6,"2NVD.UK":0.6,"NVD3.UK":0.6,"UFO":0.6,"NVDS":0.6,"NVIW.SI":0.6,"TSYW.SI":0.6,"3NVD.UK":0.6,"NVDS.UK":0.6,"NVDA":1.95,"SNVD.UK":0.6,"NVDX":0.6,"NVD2.UK":0.6}},"shareLink":"https://laohu8.com/post/518806467682904","orderFlag":false,"starInvestorRankings":[],"featuresForAnalytics":[],"commentAndTweetFlag":false,"upFlag":false,"length":250,"displayRows":4,"foldSize":0,"authorId":"4125884878211772"}],"position":0},{"cardType":"TWEET","cardId":"TWEET.519010181763712","cardData":[{"tweetId":"519010181763712","author":{"authorId":"3562909664933798","idStr":"3562909664933798","name":"特斯拉","avatar":"https://static.tigerbbs.com/c97d09ce1f3268f15e9bd8d11f045f8c","userType":5,"introduction":"特斯拉官方","crmLevel":1,"crmLevelSwitch":0,"individualDisplayBadges":[],"fanSize":431828,"starInvestorFlag":false,"userFollowAuthorFlag":false,"authorFollowUserFlag":false},"userFollowAuthorFlag":false,"authorFollowUserFlag":false,"title":"这些年,特斯拉为车友免费升级了多少实用功能?🧐","digest":"2022-2025年累计推送了 58次OTA远程升级,带来100+项实用功能更新 娱乐🎮出行🚘控车📲统统搞定 一次购买,更新不断,进化不停🧬 新年开新车,不花钱也能体验“新车感” 安全智能又好玩,这就是特斯拉车主们的快乐[爱你]","plainDigest":"2022-2025年累计推送了 58次OTA远程升级,带来100+项实用功能更新 娱乐🎮出行🚘控车📲统统搞定 一次购买,更新不断,进化不停🧬 新年开新车,不花钱也能体验“新车感” 安全智能又好玩,这就是特斯拉车主们的快乐[爱你]","sourceLanguage":"CN","currentLanguage":"CN","editable":false,"auditStatus":"PASSED","topFlag":false,"totalScore":0,"gmtCreate":1767686671645,"gmtModify":1767686679410,"symbols":["TSLA","TSLL"],"themeIds":[],"popularizeThemeFlag":false,"imageCount":4,"images":[{"url":"https://static.tigerbbs.com/a1ddfb3fbdc79b037d91a3ce98f2bbe3","width":"1080","height":"2340"}],"repostCount":1,"viewCount":38065,"likeCount":0,"liked":false,"collected":false,"commentCount":0,"hotComments":[],"voteFlag":false,"rewardFlag":false,"videoFlag":false,"articleFlag":false,"paperFlag":true,"essentialFlag":false,"highlightedFlag":false,"shareLink":"https://laohu8.com/post/519010181763712","orderFlag":false,"starInvestorRankings":[],"featuresForAnalytics":[],"commentAndTweetFlag":false,"upFlag":false,"length":191,"displayRows":4,"foldSize":0,"authorId":"3562909664933798"}],"position":0},{"cardType":"TWEET","cardId":"TWEET.518620697805512","cardData":[{"tweetId":"518620697805512","author":{"authorId":"4205399659440112","idStr":"4205399659440112","name":"顺势而为把握时机","avatar":"https://community-static.tradeup.com/news/default-avatar.jpg","userType":1,"introduction":"","crmLevel":6,"crmLevelSwitch":0,"individualDisplayBadges":[],"fanSize":0,"starInvestorFlag":false,"userFollowAuthorFlag":false,"authorFollowUserFlag":false},"userFollowAuthorFlag":false,"authorFollowUserFlag":false,"title":"特斯拉最近不行","digest":"截至2026年1月5日,特斯拉(TSLA)收于438.07美元,已七连跌,短期偏空,中期关键看支撑与量能变化。以下是核心结论与实操位。 一、走势速览 - 驱动:**Q4交付同比-15.6%、全年-8.6%**不及预期,政策红利消退、竞争加剧、车型迭代慢,情绪偏弱 。 - 技术:失守50日均线(445美元),RSI约45.89(中性),MACD空头,短期反弹动能不足。 - 结构:从12月近500美元回落,处于高位回调,关注430-440与400-410支撑带。 二、支撑位(由近及远) - 第一支撑:430-435美元,近期成交密集区,1月2日低点435.30美元,破位下探第二支撑。 - 第二支撑:418-424美元,周线关键位+100日均线,强支撑,失守或加速至400美元。 - 第三支撑:400-406美元,心理关口+前期平台,若放量跌破,中期转弱概率上升。 - 强支撑:360-361美元(200日均线),中期多空分水岭,接近或触及易引发技术性反弹。 三、压力位(由近及远) - 第一压力:444-449美元,50日均线+近期平台,收复转中性,受阻延续弱势。 - 第二压力:463-464美元,21日均线+前期震荡上沿,突破则缓解七连跌情绪。 - 第三压力:475-490美元,12月多次冲击未果,机构兑现区,需放量突破才有望再攻500美元。 - 强压力:500美元,心理+历史高位,年内多次承压,突破需基本面与资金共振。 四、操作建议 - 短线:以444美元为多空线,站上看463-475,止损430;跌破430则看418-424,止损406下方。 - 中线:等400-420企稳+放量止跌再布局,防守200日均线;若464放量突破,可轻仓追多,目标490-500。 - 风险:交付疲软、政策退坡、竞争加剧、马斯克舆情,控制仓位,期权交易者可结合波动率做策略 。 五、总结 短期偏空,先看","plainDigest":"截至2026年1月5日,特斯拉(TSLA)收于438.07美元,已七连跌,短期偏空,中期关键看支撑与量能变化。以下是核心结论与实操位。 一、走势速览 - 驱动:**Q4交付同比-15.6%、全年-8.6%**不及预期,政策红利消退、竞争加剧、车型迭代慢,情绪偏弱 。 - 技术:失守50日均线(445美元),RSI约45.89(中性),MACD空头,短期反弹动能不足。 - 结构:从12月近500美元回落,处于高位回调,关注430-440与400-410支撑带。 二、支撑位(由近及远) - 第一支撑:430-435美元,近期成交密集区,1月2日低点435.30美元,破位下探第二支撑。 - 第二支撑:418-424美元,周线关键位+100日均线,强支撑,失守或加速至400美元。 - 第三支撑:400-406美元,心理关口+前期平台,若放量跌破,中期转弱概率上升。 - 强支撑:360-361美元(200日均线),中期多空分水岭,接近或触及易引发技术性反弹。 三、压力位(由近及远) - 第一压力:444-449美元,50日均线+近期平台,收复转中性,受阻延续弱势。 - 第二压力:463-464美元,21日均线+前期震荡上沿,突破则缓解七连跌情绪。 - 第三压力:475-490美元,12月多次冲击未果,机构兑现区,需放量突破才有望再攻500美元。 - 强压力:500美元,心理+历史高位,年内多次承压,突破需基本面与资金共振。 四、操作建议 - 短线:以444美元为多空线,站上看463-475,止损430;跌破430则看418-424,止损406下方。 - 中线:等400-420企稳+放量止跌再布局,防守200日均线;若464放量突破,可轻仓追多,目标490-500。 - 风险:交付疲软、政策退坡、竞争加剧、马斯克舆情,控制仓位,期权交易者可结合波动率做策略 。 五、总结 短期偏空,先看","sourceLanguage":"CN","currentLanguage":"CN","editable":false,"auditStatus":"PASSED","topFlag":false,"totalScore":0,"gmtCreate":1767645589261,"gmtModify":1767645840012,"symbols":["TSLA","TSLL"],"themeIds":[],"popularizeThemeFlag":false,"imageCount":0,"images":[],"repostCount":0,"viewCount":391,"likeCount":1,"liked":false,"collected":false,"commentCount":0,"hotComments":[],"voteFlag":false,"rewardFlag":false,"videoFlag":false,"articleFlag":false,"paperFlag":true,"essentialFlag":false,"highlightedFlag":false,"shareLink":"https://laohu8.com/post/518620697805512","orderFlag":false,"starInvestorRankings":[],"featuresForAnalytics":[],"commentAndTweetFlag":false,"upFlag":false,"length":1333,"displayRows":4,"foldSize":0,"authorId":"4205399659440112"}],"position":0},{"cardType":"TWEET","cardId":"TWEET.517219642782056","cardData":[{"tweetId":"517219642782056","author":{"authorId":"3546249304196282","idStr":"3546249304196282","name":"火火兔爸","avatar":"https://static.tigerbbs.com/1914631c23e50a7645217a36cc9d9598","userType":1,"introduction":"","userGiftHeadFrame":"https://static.tigerbbs.com/b0a2963eb37c60c5d6d4a8dbcd266952","crmLevel":9,"crmLevelSwitch":1,"individualDisplayBadges":[],"fanSize":440,"starInvestorFlag":false,"userFollowAuthorFlag":false,"authorFollowUserFlag":false},"userFollowAuthorFlag":false,"authorFollowUserFlag":false,"title":"","digest":"单就特斯拉的保有数量一旦新的fsd订阅量大幅上升都可以很好的提升利润","plainDigest":"单就特斯拉的保有数量一旦新的fsd订阅量大幅上升都可以很好的提升利润","sourceLanguage":"CN","currentLanguage":"CN","editable":false,"auditStatus":"PASSED","topFlag":false,"totalScore":0,"gmtCreate":1767249585789,"gmtModify":1767249588402,"symbols":["TSLL"],"themeIds":[],"popularizeThemeFlag":false,"imageCount":0,"images":[],"repostCount":0,"viewCount":1218,"likeCount":1,"liked":false,"collected":false,"commentCount":2,"hotComments":[{"id":"517301153132856","author":{"authorId":"4095221978421840","idStr":"4095221978421840","name":"VIX模式","avatar":"https://static.tigerbbs.com/c0d8923140f63caec1e5b06a7ad3ddfb","userType":1,"introduction":"","crmLevel":1,"crmLevelSwitch":0,"fanSize":0,"starInvestorFlag":false},"content":"明年是不是着重做多特斯拉","plainContent":"明年是不是着重做多特斯拉","likeCount":0,"commentType":"hot","coins":0}],"voteFlag":false,"rewardFlag":false,"videoFlag":false,"articleFlag":false,"paperFlag":false,"essentialFlag":false,"highlightedFlag":false,"repostId":"1187057628","repostType":2,"repostNewsData":{"id":"1187057628","kind":"news","pubTimestamp":1767243974,"share":"https://www.laohu8.com/m/news/1187057628?lang=zh_CN&edition=full","pubTime":"2026-01-01 13:06","market":"us","language":"zh","title":"马斯克10年梦成真!特斯拉全球首次自动驾驶横穿美国,人类0次接管","url":"https://stock-news.laohu8.com/highlight/detail?id=1187057628","media":"新智元","summary":"刚刚,特斯拉FSD,完成全球首个完全自动驾驶的横穿美国。从美国西海岸开到东海岸,2天20小时,人类0次接管。特斯拉官方账号,表扬了这次壮举。全球首次人类零接管下面这份数据,让人难以抑制心头的震撼。从2016年,特斯拉的FSD系统就开始宣传「零干预横贯美国」的目标。然而David Moss晒出的仪表盘显示,FSD V14千真万确完成了100%的完全自动驾驶。尽管特斯拉坚信端到端神经网络技术,但这绝非自动驾驶领域的共识方案。","content":"<html><head></head><body><blockquote><p>导读:2026年第一天,自动驾驶迎来历史时刻——特斯拉FSD完成人类首次「零接管」横穿美国!全球科技圈都被引爆了,马斯克端到端自动驾驶彻底胜利。方向盘,可以退出历史舞台了?</p></blockquote><p style=\"text-align: justify;\">刚刚,特斯拉FSD,完成全球首个完全自动驾驶的横穿美国。</p><p style=\"text-align: justify;\">从今天起,人类的自动驾驶,到达了全新的里程碑!</p><p style=\"text-align: justify;\">就在2025年的最后一天,当全世界都在准备倒数跨年时,车主David Moss静悄悄地扔出了一枚深水炸弹——</p><p style=\"text-align: justify;\"><strong>他驾驶搭载FSD V14.2的Model 3,完成了全球首次、经由第三方数据验证的「零接管」横贯美国之旅。</strong></p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/b6aee72268a9f7fe87a51dfbed54d641\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"907\"/></p><p>从美国西海岸开到东海岸,2天20小时,人类0次接管。</p><p>物理世界的「自动驾驶奇点」,终于降临!</p><p style=\"text-align: justify;\">这条推特,也彻底引爆了全球科技圈和AI圈。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/861c807c134505ea2367214c8df763dd\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"810\"/></p><p style=\"text-align: justify;\">由此,他也成为全世界第一个全程凭借自动驾驶横穿美国的人。</p><p style=\"text-align: justify;\">可以说,这是特斯拉正式通过了公路上的图灵测试。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/f1f1dcedc4f2917710ec0126fe4846d2\" alt=\"\" title=\"\" tg-width=\"640\" tg-height=\"356\"/></p><p style=\"text-align: justify;\">这场AI主导的公路旅行,直接震撼了全球特斯拉车主。</p><p style=\"text-align: justify;\">前特斯拉AI总监Karpathy兴奋高呼:这一刻终于来了,这是端到端神经网络的胜利,这是「软件2.0」在物理世界的完全接管,不再需要人类写下的规则!</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/a379d8ff233b39e51f1ade3558c5897f\" alt=\"\" title=\"\" tg-width=\"1062\" tg-height=\"490\"/></p><p style=\"text-align: justify;\">特斯拉官方账号,表扬了这次壮举。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/92fc3958e2cc9dca7573da1973f58aba\" alt=\"\" title=\"\" tg-width=\"1074\" tg-height=\"311\"/></p><p style=\"text-align: justify;\">一位特斯拉车主赞叹:「我们已步入自动驾驶穿越美洲大陆的时代。」</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/71cd22a3869044eac05eaaf7c37ef793\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"382\"/></p><p style=\"text-align: justify;\">特斯拉掌门人马斯克,也激动转发莫斯的推文:「酷!」</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/d09bb212cefa782616bc27450f3eeeec\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"1247\"/></p><p style=\"text-align: justify;\">十年前,马斯克许下「Coast-to-Coast」的诺言,2026年1月1日,终于实现了!</p><p style=\"text-align: justify;\">或者真如Karpathy所说:从此,方向盘只是车上的一个装饰品?</p><h2 id=\"id_3148617888\">全球首次人类零接管</h2><p style=\"text-align: justify;\">下面这份数据,让人难以抑制心头的震撼。</p><ul style=\"\"><li><p style=\"text-align: justify;\"><strong>总里程:2732.4英里(约等于4397公里)</strong></p></li><li><p style=\"text-align: justify;\"><strong>耗时:2天20小时</strong></p></li><li><p style=\"text-align: justify;\"><strong>软件版本:FSD v14.2</strong></p></li><li><p style=\"text-align: justify;\"><strong>人工接管:0</strong></p></li></ul><p style=\"text-align: justify;\">当特斯拉从v12开始抛弃传统的C++,转向端到端神经网络,AI就从数百万小时的视频中,真正学会了开车。</p><p style=\"text-align: justify;\">在这场横跨美国大陆的旅途中,David Moss没有任何一刻,触摸车里的方向盘,或者踩过踏板!</p><p style=\"text-align: justify;\">想象一下:坐在驾驶座上,盯着方向盘整整<strong>68个小时</strong>(2天20小时),看着它自行转动,穿过繁忙的洛杉矶街道,汇入州际高速,避让加州的摩托车手,在德克萨斯的暴雨中稳住车身,最后停在南卡罗来纳州的海滩边。</p><p style=\"text-align: justify;\">他从洛杉矶的特斯拉餐厅出发,最终到达南卡罗来纳州默特尔海滩,穿越了24个州。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/697d95147dfe779b7963f104ea9f94dd\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"474\"/></p><p style=\"text-align: justify;\">如果你亲自开过这段行程,就会明白全程的路况有多么复杂。然而从加州的高速公路,到中部的城市街道,再到东海岸的复杂路况,FSD一次性全部搞定了!</p><p style=\"text-align: justify;\">天气多变,交通拥挤,甚至夜间驾驶、自动化充电,都没让系统掉链子。</p><p>Moss评价说——整个过程中,从未出现过一次险情,即使在人类驾驶员中,这也实属罕见。 </p><p style=\"text-align: justify;\">对于好奇的网友,Moss表示,你可以登录FSD数据库,验证所有数据。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/f9f72f7c732a5bc94e624b9f0a60cfb8\" alt=\"\" title=\"\" tg-width=\"1073\" tg-height=\"238\"/></p><p>同时,David Moss晒出了充电记录。注意,在所有站点的停车,也都是由特斯拉FSD自动完成的。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/bf8a1fe029809749e7d323cdd653a35b\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"1064\"/></p><p style=\"text-align: justify;\">这次横穿美国大陆,不仅体现了FSD V14.2的技术能力,也向整个行业证实——</p><p style=\"text-align: justify;\">即使在现实的复杂场景,L4自动驾驶也有可能实现!</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/a56403799ea716097a228bec0fbbd065\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"1426\"/></p><p style=\"text-align: justify;\">十几年前,这样的壮举还只是工程师的技术梦想。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/8729c8c5dfe90f0d2ccf4866b4501344\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"584\"/></p><p style=\"text-align: justify;\">从2016年,特斯拉的FSD系统就开始宣传「零干预横贯美国」的目标。</p><p style=\"text-align: justify;\">在发布Autopilot 2.0时,Elon Musk就放话,说2017年底就能实现。</p><p style=\"text-align: justify;\">这是一个迟到了八年的承诺,但当它终于兑现时,仍然让人感到吃惊!</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/7e1444fce4aaab9815356436fb17ba34\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"628\"/></p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/bac076faebb192fe4c4e64c7735c1405\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"1356\"/></p><h2 id=\"id_3795981535\">一位特斯拉FSD的死忠粉</h2><p style=\"text-align: justify;\">其实在25年底,David Moss就曾创下纪录。</p><p style=\"text-align: justify;\">当时,他在特斯拉FSD V14上,连续驾驶了超过10000英里,且全程无干预,实现了真正的100%自动驾驶。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/7c930a14b2fd92448fa1d79c49751658\" alt=\"\" title=\"\" tg-width=\"1075\" tg-height=\"1440\"/></p><p style=\"text-align: justify;\">当时的路线图是这样的。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/aa4ed0e35d8ab465e146ace97971e981\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"451\"/></p><p style=\"text-align: justify;\">而这个消息出来后,网友们纷纷表示,不可能,这绝不可能!</p><p style=\"text-align: justify;\">有人说,自己每天都在用FSD 14.2.2.1,虽然体验很棒,但绝不可能实现完全自动驾驶。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/e4365efb77c0bb39d6e88e7d8355f42e\" alt=\"\" title=\"\" tg-width=\"1065\" tg-height=\"319\"/></p><p style=\"text-align: justify;\">然而David Moss晒出的仪表盘显示,FSD V14千真万确完成了100%的完全自动驾驶。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/93a34c66a66af02c78abea3bd7b4b2d5\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"608\"/></p><p style=\"text-align: justify;\">在去年年底,他就立下宏愿:成为第一个完全依靠FSD用自动驾驶横跨美国(洛杉矶→佛罗里达)的人。</p><p style=\"text-align: justify;\">时隔一年,他果然完成了这个目标,实现了一个更宏大的路线图。</p><p style=\"text-align: justify;\">这完全出于他对驾驶的热爱,并不是为了炒作。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/2943e5dc9b0c1d42d1dae03f67da7e1c\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"600\"/></p><h2 id=\"id_2196220549\">马斯克:那个「该死的」2017 预言</h2><p style=\"text-align: justify;\">回到2016年10月。</p><p style=\"text-align: justify;\">彼时,马斯克意气风发,豪言:「<strong>到2017年底,特斯拉将能够从洛杉矶自动驾驶到纽约,全程哪怕你碰一下方向盘都算我输</strong>。」</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/1ea329f88fcddb10764ec5b1a44ff585\" alt=\"\" title=\"\" tg-width=\"1008\" tg-height=\"356\"/></p><p style=\"text-align: justify;\">后来的故事我们都知道了。</p><p style=\"text-align: justify;\">2017年过去了,2020年过去了,甚至到了2024年,马斯克不断跳票!</p><p style=\"text-align: justify;\">这个承诺就像是一个「永远的明年」。</p><p style=\"text-align: justify;\">由于技术路线的反复横跳(从雷达+视觉到纯视觉,从规则代码到神经网络),特斯拉的自动驾驶曾一度陷入瓶颈,甚至被谷歌旗下的Waymo在无人出租车领域抢尽风头。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/a223047232c267c5e5c05149af7febc5\" alt=\"Gemini生成的特斯拉自动驾驶技术路线图\" title=\"Gemini生成的特斯拉自动驾驶技术路线图\" tg-width=\"1024\" tg-height=\"559\"/><span>Gemini生成的特斯拉自动驾驶技术路线图</span></p><p style=\"text-align: justify;\">直到FSD V12 版本的出现,特斯拉彻底抛弃了原来的代码逻辑,转向了「端到端」神经网络。</p><p style=\"text-align: justify;\">简单说,就是让AI像人类一样,直接通过看视频学会开车,而不是由工程师一行行写代码告诉它「红灯停、绿灯行」。</p><p style=\"text-align: justify;\">尽管特斯拉坚信端到端神经网络技术,但这绝非自动驾驶领域的共识方案。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/155a58ae4ab1b842b1058ea332966eb3\" alt=\"\" title=\"\" tg-width=\"1080\" tg-height=\"780\"/></p><p style=\"text-align: justify;\">大多数其他自动驾驶研发公司都采用传感器密集型、模块化的驾驶方式。虽然这类系统在初期开发和调试可能更容易,但其复杂性也不容忽视。</p><p style=\"text-align: justify;\">特斯拉AI负责人Ashok Elluswam,在国际计算机视觉大会ICCV介绍了端到端方案的优势:</p><ul style=\"\"><li><p style=\"text-align: justify;\"><strong>将人类价值观系统化极其困难,从数据中了解它们则容易得多。</strong></p></li><li><p style=\"text-align: justify;\"><strong>感知、预测和规划之间的接口定义不明确。在端到端架构中,梯度从控制端一直流向传感器输入端,从而整体优化整个网络。</strong></p></li><li><p style=\"text-align: justify;\"><strong>易于扩展,可处理现实世界机器人技术的庞大而长尾需求。</strong></p></li><li><p style=\"text-align: justify;\"><strong>具有确定性延迟的同构计算。</strong></p></li><li><p style=\"text-align: justify;\"><strong>总的来说,相对于过去的苦涩教训,这种方法在规模化方面处于正确的位置</strong>。</p></li></ul><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/835c599dc7d046ce49f47a8bcc5a41db\" alt=\"\" title=\"\" tg-width=\"1057\" tg-height=\"406\"/></p><p style=\"text-align: justify;\">更绝的是,为了自动驾驶数据打造的神经网络<strong>「世界模拟器」</strong>,同样可以模拟多种真实场景,训练擎天柱。。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/f93cfa8c47ff761badcba3317ba72fba\" alt=\"\" title=\"\" tg-width=\"878\" tg-height=\"516\"/></p><p style=\"text-align: justify;\">马斯克「世界模拟器」首曝,1天蒸馏人类500年驾驶经验!擎天柱同脑进化</p><p style=\"text-align: justify;\">而这次「人类零接管」的关键在于「端到端」的最后一块拼图。</p><p style=\"text-align: justify;\">在V14之前,特斯拉的AI虽然眼神好使(视觉感知强),但脑子里的地图还是传统的导航模块。</p><p style=\"text-align: justify;\">这就好比一个老司机虽然车技好,但他脑子里只有一张死板的纸质地图,一旦遇到修路或者地图没更新,就容易发懵。</p><p style=\"text-align: justify;\">而在V14.2中,特斯拉将<strong>导航和路径规划也整合进了神经网络</strong>。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/00978449f215761104e96a37e5633761\" alt=\"\" title=\"\" tg-width=\"962\" tg-height=\"481\"/></p><p style=\"text-align: justify;\">现在的FSD不再是「看着地图开车」,而是像本地人一样,能根据眼前的路况实时理解该怎么走。</p><p style=\"text-align: justify;\">一次成功的「零接管」,不等于这套系统已经完美。</p><p style=\"text-align: justify;\">统计学告诉我们,如果事故率是万分之一,那么跑一次几千公里的长途可能正好没遇上,但这并不代表它能安全应对几百万辆车的日常通勤。</p><p style=\"text-align: justify;\">不过,FSD V14.2的这次表现,最大的意义在于它有力回应了「纯视觉方案无法实现长途全自动」的质疑。</p><p style=\"text-align: justify;\">它证明了不需要昂贵的激光雷达,不需要高精地图,仅凭摄像头和算力,AI真的可以处理从繁华都市到荒凉公路的几乎所有场景。</p><p style=\"text-align: justify;\"><strong>对于普通人来说,这意味着什么?</strong></p><p style=\"text-align: justify;\">官方仍是<strong>SAE L2(需监督),</strong>但车辆完成<strong>100%驾驶任务,</strong>驾驶员仅作安全监督,完全有可能。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/22b1803d0dad2bdae4704e43fad71ebb\" alt=\"\" title=\"\" tg-width=\"1024\" tg-height=\"437\"/></p><p style=\"text-align: justify;\">也许,还要等上几个版本,甚至要等到硬件Hardware 5.0的普及,我们才能真正放心地在车里睡大觉。</p><p style=\"text-align: justify;\">但看着David Moss那辆横跨大陆的Model 3,那个曾经被嘲笑为「科幻小说」的未来,确实已经把轮胎压在了现实的沥青路上。</p><p class=\"t-img-caption\"><img src=\"https://static.tigerbbs.com/5d5e84f22c6e2c4b6d1c45f6293cf6ef\" alt=\"\" title=\"\" tg-width=\"640\" tg-height=\"357\"/></p></body></html>","source":"lsy1569730104218","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>马斯克10年梦成真!特斯拉全球首次自动驾驶横穿美国,人类0次接管</title>\n<style 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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马斯克10年梦成真!特斯拉全球首次自动驾驶横穿美国,人类0次接管\n</h2>\n\n<h4 class=\"meta\">\n\n\n2026-01-01 13:06 北京时间 <a href=https://mp.weixin.qq.com/s/PPJpXH4kNqAa3DgNqONYGA><strong>新智元</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>导读:2026年第一天,自动驾驶迎来历史时刻——特斯拉FSD完成人类首次「零接管」横穿美国!全球科技圈都被引爆了,马斯克端到端自动驾驶彻底胜利。方向盘,可以退出历史舞台了?刚刚,特斯拉FSD,完成全球首个完全自动驾驶的横穿美国。从今天起,人类的自动驾驶,到达了全新的里程碑!就在2025年的最后一天,当全世界都在准备倒数跨年时,车主David Moss静悄悄地扔出了一枚深水炸弹——他驾驶搭载FSD ...</p>\n\n<a href=\"https://mp.weixin.qq.com/s/PPJpXH4kNqAa3DgNqONYGA\">网页链接</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/8b14046a5c125b858022492698a79384","relate_stocks":{"TSLA":"特斯拉"},"source_url":"https://mp.weixin.qq.com/s/PPJpXH4kNqAa3DgNqONYGA","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1187057628","content_text":"导读:2026年第一天,自动驾驶迎来历史时刻——特斯拉FSD完成人类首次「零接管」横穿美国!全球科技圈都被引爆了,马斯克端到端自动驾驶彻底胜利。方向盘,可以退出历史舞台了?刚刚,特斯拉FSD,完成全球首个完全自动驾驶的横穿美国。从今天起,人类的自动驾驶,到达了全新的里程碑!就在2025年的最后一天,当全世界都在准备倒数跨年时,车主David Moss静悄悄地扔出了一枚深水炸弹——他驾驶搭载FSD V14.2的Model 3,完成了全球首次、经由第三方数据验证的「零接管」横贯美国之旅。从美国西海岸开到东海岸,2天20小时,人类0次接管。物理世界的「自动驾驶奇点」,终于降临!这条推特,也彻底引爆了全球科技圈和AI圈。由此,他也成为全世界第一个全程凭借自动驾驶横穿美国的人。可以说,这是特斯拉正式通过了公路上的图灵测试。这场AI主导的公路旅行,直接震撼了全球特斯拉车主。前特斯拉AI总监Karpathy兴奋高呼:这一刻终于来了,这是端到端神经网络的胜利,这是「软件2.0」在物理世界的完全接管,不再需要人类写下的规则!特斯拉官方账号,表扬了这次壮举。一位特斯拉车主赞叹:「我们已步入自动驾驶穿越美洲大陆的时代。」特斯拉掌门人马斯克,也激动转发莫斯的推文:「酷!」十年前,马斯克许下「Coast-to-Coast」的诺言,2026年1月1日,终于实现了!或者真如Karpathy所说:从此,方向盘只是车上的一个装饰品?全球首次人类零接管下面这份数据,让人难以抑制心头的震撼。总里程:2732.4英里(约等于4397公里)耗时:2天20小时软件版本:FSD v14.2人工接管:0当特斯拉从v12开始抛弃传统的C++,转向端到端神经网络,AI就从数百万小时的视频中,真正学会了开车。在这场横跨美国大陆的旅途中,David Moss没有任何一刻,触摸车里的方向盘,或者踩过踏板!想象一下:坐在驾驶座上,盯着方向盘整整68个小时(2天20小时),看着它自行转动,穿过繁忙的洛杉矶街道,汇入州际高速,避让加州的摩托车手,在德克萨斯的暴雨中稳住车身,最后停在南卡罗来纳州的海滩边。他从洛杉矶的特斯拉餐厅出发,最终到达南卡罗来纳州默特尔海滩,穿越了24个州。如果你亲自开过这段行程,就会明白全程的路况有多么复杂。然而从加州的高速公路,到中部的城市街道,再到东海岸的复杂路况,FSD一次性全部搞定了!天气多变,交通拥挤,甚至夜间驾驶、自动化充电,都没让系统掉链子。Moss评价说——整个过程中,从未出现过一次险情,即使在人类驾驶员中,这也实属罕见。 对于好奇的网友,Moss表示,你可以登录FSD数据库,验证所有数据。同时,David Moss晒出了充电记录。注意,在所有站点的停车,也都是由特斯拉FSD自动完成的。这次横穿美国大陆,不仅体现了FSD V14.2的技术能力,也向整个行业证实——即使在现实的复杂场景,L4自动驾驶也有可能实现!十几年前,这样的壮举还只是工程师的技术梦想。从2016年,特斯拉的FSD系统就开始宣传「零干预横贯美国」的目标。在发布Autopilot 2.0时,Elon Musk就放话,说2017年底就能实现。这是一个迟到了八年的承诺,但当它终于兑现时,仍然让人感到吃惊!一位特斯拉FSD的死忠粉其实在25年底,David Moss就曾创下纪录。当时,他在特斯拉FSD V14上,连续驾驶了超过10000英里,且全程无干预,实现了真正的100%自动驾驶。当时的路线图是这样的。而这个消息出来后,网友们纷纷表示,不可能,这绝不可能!有人说,自己每天都在用FSD 14.2.2.1,虽然体验很棒,但绝不可能实现完全自动驾驶。然而David Moss晒出的仪表盘显示,FSD V14千真万确完成了100%的完全自动驾驶。在去年年底,他就立下宏愿:成为第一个完全依靠FSD用自动驾驶横跨美国(洛杉矶→佛罗里达)的人。时隔一年,他果然完成了这个目标,实现了一个更宏大的路线图。这完全出于他对驾驶的热爱,并不是为了炒作。马斯克:那个「该死的」2017 预言回到2016年10月。彼时,马斯克意气风发,豪言:「到2017年底,特斯拉将能够从洛杉矶自动驾驶到纽约,全程哪怕你碰一下方向盘都算我输。」后来的故事我们都知道了。2017年过去了,2020年过去了,甚至到了2024年,马斯克不断跳票!这个承诺就像是一个「永远的明年」。由于技术路线的反复横跳(从雷达+视觉到纯视觉,从规则代码到神经网络),特斯拉的自动驾驶曾一度陷入瓶颈,甚至被谷歌旗下的Waymo在无人出租车领域抢尽风头。Gemini生成的特斯拉自动驾驶技术路线图直到FSD V12 版本的出现,特斯拉彻底抛弃了原来的代码逻辑,转向了「端到端」神经网络。简单说,就是让AI像人类一样,直接通过看视频学会开车,而不是由工程师一行行写代码告诉它「红灯停、绿灯行」。尽管特斯拉坚信端到端神经网络技术,但这绝非自动驾驶领域的共识方案。大多数其他自动驾驶研发公司都采用传感器密集型、模块化的驾驶方式。虽然这类系统在初期开发和调试可能更容易,但其复杂性也不容忽视。特斯拉AI负责人Ashok Elluswam,在国际计算机视觉大会ICCV介绍了端到端方案的优势:将人类价值观系统化极其困难,从数据中了解它们则容易得多。感知、预测和规划之间的接口定义不明确。在端到端架构中,梯度从控制端一直流向传感器输入端,从而整体优化整个网络。易于扩展,可处理现实世界机器人技术的庞大而长尾需求。具有确定性延迟的同构计算。总的来说,相对于过去的苦涩教训,这种方法在规模化方面处于正确的位置。更绝的是,为了自动驾驶数据打造的神经网络「世界模拟器」,同样可以模拟多种真实场景,训练擎天柱。。马斯克「世界模拟器」首曝,1天蒸馏人类500年驾驶经验!擎天柱同脑进化而这次「人类零接管」的关键在于「端到端」的最后一块拼图。在V14之前,特斯拉的AI虽然眼神好使(视觉感知强),但脑子里的地图还是传统的导航模块。这就好比一个老司机虽然车技好,但他脑子里只有一张死板的纸质地图,一旦遇到修路或者地图没更新,就容易发懵。而在V14.2中,特斯拉将导航和路径规划也整合进了神经网络。现在的FSD不再是「看着地图开车」,而是像本地人一样,能根据眼前的路况实时理解该怎么走。一次成功的「零接管」,不等于这套系统已经完美。统计学告诉我们,如果事故率是万分之一,那么跑一次几千公里的长途可能正好没遇上,但这并不代表它能安全应对几百万辆车的日常通勤。不过,FSD V14.2的这次表现,最大的意义在于它有力回应了「纯视觉方案无法实现长途全自动」的质疑。它证明了不需要昂贵的激光雷达,不需要高精地图,仅凭摄像头和算力,AI真的可以处理从繁华都市到荒凉公路的几乎所有场景。对于普通人来说,这意味着什么?官方仍是SAE L2(需监督),但车辆完成100%驾驶任务,驾驶员仅作安全监督,完全有可能。也许,还要等上几个版本,甚至要等到硬件Hardware 5.0的普及,我们才能真正放心地在车里睡大觉。但看着David Moss那辆横跨大陆的Model 3,那个曾经被嘲笑为「科幻小说」的未来,确实已经把轮胎压在了现实的沥青路上。","news_type":1,"symbols_score_info":{"TSLA":2}},"shareLink":"https://laohu8.com/post/517219642782056","orderFlag":false,"starInvestorRankings":[],"featuresForAnalytics":[],"commentAndTweetFlag":false,"upFlag":false,"length":65,"displayRows":4,"foldSize":0,"authorId":"3546249304196282"}],"position":0}],"size":20},"newsData":null,"noticeData":{"listData":[],"currentPage":1,"bottom":true},"companyData":{"profile":{"stockEarnings":[{"period":"1week","weight":-0.0963},{"period":"1month","weight":-0.1436},{"period":"3month","weight":-0.131},{"period":"6month","weight":0.5987},{"period":"1year","weight":-0.3746},{"period":"ytd","weight":-0.0764}],"compareEarnings":[{"period":"1week","weight":0.007},{"period":"1month","weight":0.0089},{"period":"3month","weight":0.0278},{"period":"6month","weight":0.1054},{"period":"1year","weight":0.162},{"period":"ytd","weight":0.0145}],"compareStock":{"symbol":"SPY","name":"标普500ETF"},"yearOnYearQuotes":[{"month":1,"riseRate":0.25,"avgChangeRate":0.038226},{"month":2,"riseRate":0.666667,"avgChangeRate":-0.037295},{"month":3,"riseRate":0,"avgChangeRate":-0.169318},{"month":4,"riseRate":0.666667,"avgChangeRate":-0.067039},{"month":5,"riseRate":0.666667,"avgChangeRate":0.246193},{"month":6,"riseRate":0.666667,"avgChangeRate":0.141424},{"month":7,"riseRate":0.666667,"avgChangeRate":0.067997},{"month":8,"riseRate":0.333333,"avgChangeRate":-0.032513},{"month":9,"riseRate":0.5,"avgChangeRate":0.255611},{"month":10,"riseRate":0.25,"avgChangeRate":-0.158807},{"month":11,"riseRate":0.5,"avgChangeRate":0.180741},{"month":12,"riseRate":0.75,"avgChangeRate":-0.04408}],"exchange":"NASDAQ","name":"2倍做多TSLA 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