特斯拉通过“物理图灵测试”！英伟达机器人主管爆吹，圣诞节刷屏了

量子位2025-12-26

Jay henry 发自凹非寺量子位 | 公众号 QbitAI特斯拉FSD v14，首个通过“物理图灵测试”的AI。为特斯拉“颁发”这一殊荣的并非别人，而是英伟达大名鼎鼎的机器人主管——Jim Fan。平安夜前夕，这位英伟达Project GR00T的领军人物，在亲眼看到自家特斯拉的一路自主护送自己回家后，大受震撼：我入手特斯拉比较晚，但却是最早体验FSDv14的用户之一。这可能是我第一次真正...

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Nvidia's robotics director exploded, and Christmas flooded the screen","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"NVIW.SI":0.6,"NVDU":0.6,"3NVD.UK":0.6,"NVDS":0.6,"NVDY":0.6,"TSLA":1.98,"TSYW.SI":0.6,"SNVD.UK":0.6,"NVD2.UK":0.6,"2NVD.UK":0.6,"NVDS.UK":0.6,"NVD3.UK":0.6,"NVDX":0.6,"NVDA":0.9,"NVD":0.6,"NVDD":0.6},"content_text":"Jay henry 发自 凹非寺量子位 | 公众号 QbitAI特斯拉FSD v14，首个通过“物理图灵测试”的AI。为特斯拉“颁发”这一殊荣的并非别人，而是英伟达大名鼎鼎的机器人主管——Jim Fan。平安夜前夕，这位英伟达Project GR00T的领军人物，在亲眼看到自家特斯拉的一路自主护送自己回家后，大受震撼：我入手特斯拉比较晚，但却是最早体验FSDv14的用户之一。这可能是我第一次真正感受到通过物理图灵测试的AI：结束一天漫长的工作后，你只需按下一个按钮，放松地靠在座椅上，完全分不出开车的是神经网络还是真人司机。Jim Fan表示，FSD带来的第一感觉是“不可思议”，并且很快就已经渗透进了他的生活，甚至开始有点“上瘾”。一开始你会觉得这不太真实，然后它就成了日常。再然后，就像智能手机一样，一旦失去它，你就会非常难受。这就是人类如何被重新塑造，并最终沉迷于技术。当然，FSD v14.2.2不是独属于Jim Fan的专属礼物。在陆续收到新版FSD推送后，特斯拉车主们的反馈也迅速刷屏——一句话总结：玩疯了。特斯拉圣诞狂欢首个得到英伟达机器人主管“背书”、被称为通过“物理图灵测试”的AI，在这个圣诞节火遍全网。这个圣诞节，特斯拉给车主们送来了一波至尊升级，网友一顿测试下来，结论几乎是清一色的：满意满意，相当满意，绝对是迄今为止最好的一版FSD。看到这一幕，老马自然更是高兴坏了，开始在社交平台上疯狂转发各类车主分享视频。在这批“老马严选”中，FSD的表现相当吸睛。但更值得关注的，或许是车主们的反应——全部异常兴奋，甚至“吓”坏了的那种。比如这位花臂老哥，发现FSD能读懂停车场显示屏，在识别到“车位已满”后果断跳过该楼层，激动得像看到自家孩子考了满分。下面这位小姐姐最开始没感到有啥变化，但一开始变道就出现了端倪——一秒进入“老司机”模式，说换就换，相当果断，不再打大半天转向灯。如果说这些还只是“懂车人”的兴奋，那下面这段视频就更有反差感了。车主拉上了自己从未体验过自动驾驶的奶奶，上来就给老人家配置拉满，体验最新最强FSD，直接给奶奶整出了“恐怖谷效应”。事实上，在新版FSD彻底火遍全网之前，马斯克本人早已抢先“上车”。当晚，他在社交平台发文称，自己亲自体验了一次无安全员的Robotaxi测试，并直言体验近乎“完美”。周日，我坐在副驾驶座上，一辆没有安全监控系统的特斯拉载着我在奥斯汀转了一圈，全程驾驶表现完美。这一帖子下面，特斯拉AI总监Ashok Elluswamy发布了自己的体验视频，用词同样难掩兴奋。这是一次令人惊叹的体验！当然，“老马严选”的车主，可能存在幸存者偏差；特斯拉高管站台，也不够令人信服。但从其他网友的实测反馈来看，新版FSD这一个个“惊喜”背后，的确有迹可循。旧版本的老克星——死胡同场景，基本已经能解决了：雨天，车流巨大、拥堵至极的曼哈顿街头，依然能注意到警车，并且主动避让：在狭窄车道多盲区的情况下，能及时识别到左侧有行人出现：整体看下来，网友们的体验反馈集中在两方面：更像老司机：变道丝滑没有犹豫，速度也更合适。能明显感觉到决策过程更快，并且会果断执行。脑子更灵光：旁边车道有摩托车、维修车辆和人员时，会早早留出空间。而这些叠加在一起，最终体现为长时间驾驶可靠性的大幅提升。我憋不住了：我的特斯拉第一次载着我们全家，从自家车道一路开到父母家，整整一个半小时车程……我一次都没碰方向盘。本月初，马斯克曾放下豪言：要在三周内彻底实现奥斯汀区域Robotaxi的无人驾驶，移除安全监控，副驾驶也不再坐人。而现在看来，新版FSD正在把这句豪言化为现实——不仅远超车主预期，甚至让英伟达机器人主管，都直呼不可思议。特斯拉如期而至的这份“圣诞礼物”，或许是自动驾驶迈向新阶段的，又一次涌现时刻。FSDV14.2.2这波FSD（监督版）v14.2.2更新，核心变化集中在神经网络视觉编码器的升级，整体感知与理解能力明显增强。新版本利用更高分辨率视觉输入，强化了对紧急车辆、道路障碍物以及人体手势等复杂场景的识别能力。比如，在Reddit网友分享的案例中，新版FSD展现了对小动物等异常交通行动者的避让能力。而在特殊车辆识别与响应策略上，v14.2.2对警车、消防车、救护车等场景进行了专门优化，新增靠边停车或主动避让紧急车辆的决策与执行逻辑。在导航与路径规划层面，v14.2.2引入了更动态的规划能力，可实时应对拥堵、临时绕行等路况变化，而不再完全依赖预设路径。泊车能力也是本次更新的重要增强方向，系统新增了“到达选项”，可根据个人偏好选择停车场、路边或地下车库等不同到达方式，导航终点会随之动态调整。一位网友分享了FSD v14.2.2在自家车库的倒车入库的视频，哪怕车道上还停着另一辆车，也非常丝滑。同时，FSD会记忆并绑定车主的到达偏好与常用停车位置，并保存到具体目的地。后续由推理模型评估可行的到达方案，并给出一个默认推荐选项，从而减少人工干预。在驾驶风格控制上，FSD本次全量推送了两种新的速度模式，相比此前的CHILL（冷静）模式，风格区分更加明确：SLOTH模式：整体速度更低，车道选择与决策更保守；MADMAX模式：速度更高，变道更积极。需要注意的是，特斯拉也强调，单车的实际驾驶行为仍会受到车主画像的显著影响。用户历史驾驶越激进，系统允许的最高速度与决策风格也会随之调整，某种程度上是“因人而异”的自适应策略。此外，“启动自动驾驶”按钮中的刹车确认机制已默认关闭，用户无需再通过踩下并松开刹车来确认，只需在触控屏上操作即可进入自动驾驶状态。虽然FSD v14.2.2这次的更新，表面还是一次基于FSDv14版本的微调，但配上老马高强度推特宣发的佐料，剑指Waymo的意图已经非常明显了。和Waymo大战已经硝烟弥漫先说结论：在Robotaxi这条赛道上，Waymo仍然占据先机，是当前北美市场在落地规模和市场份额上的绝对领先者；而特斯拉正凭借FSD的持续演进，在规模化路径上加速追赶。从奥斯汀这个近期最受关注的战场来看，差距依然清晰。特斯拉自今年6月在奥斯汀启动Robotaxi服务以来，目前部署规模约30辆左右。而Waymo早在3月就已在当地上线，当前在运营的自动驾驶车辆接近200辆。如果把视角拉到全美范围，Waymo的领先优势更加明显。除奥斯汀外，Waymo还已在菲尼克斯、旧金山、洛杉矶和亚特兰大提供Robotaxi服务，车队总规模超过2500辆。同时，Waymo还计划在2026年扩展至另外20座城市，其中包括达拉斯、华盛顿、迈阿密，甚至伦敦。在运营与营收层面，Waymo也已经跑在前面。其每周付费行程超过45万单，2025年全年完成约1400万次出行；自2020年启动Robotaxi业务以来，累计出行次数已超过2000万次。相比之下，特斯拉的运营版图仍然相当有限，目前只覆盖德州奥斯汀以及旧金山湾区的部分区域。今年10月，在特斯拉第三季度财报电话会上，马斯克曾表示，预计将在年底前在内华达州、佛罗里达州和亚利桑那州推出Robotaxi服务。但截至12月中旬，这一目标仍未兑现。在加州，根据CPUC和加州机动车管理局（DMV）的说法，特斯拉尚未获得运营商业化Robotaxi服务所需的许可，这也直接限制了其扩张节奏。不过，随着FSD能力的持续提升，以及Waymo在旧金山大停电事件中的失误被放大讨论，特斯拉在舆论和用户层面的关注度正在明显上升。根据Apptopia数据，自9月上线以来，截至12月12日，TeslaRobotaxi应用累计安装量已达52.9万次，过去30天的日均下载量为2790次。作为对比，Waymo应用在同一时间段内的日均下载量为24831次。虽然差距依旧明显，但特斯拉的增长趋势正在形成。在技术层面，双方的分歧也逐渐走向台前。最近，马斯克在X上公开回应了好兄弟、特斯拉前AI负责人安德烈·卡帕西（AndrejKarpathy）的相关观点。一年前，卡帕西曾表示：Waymo的问题在硬件，特斯拉的问题在软件。近期，有网友询问喜提特斯拉新车的卡帕西是否仍然坚持这一判断。卡帕西的回应是：Waymo和特斯拉的驾驶体验都已经接近“完美驾驶”，确实存在差异，但只有在特定场景中才会显现。而旧金山停电事件就是其中一个例子。这一表态，被部分人解读为：特斯拉FSD仍略逊于Waymo。对此，马斯克直接反驳称：安子的认知在这一点上已经有些过时了。自他离开之后，特斯拉的AI软件已经取得了巨大的进步，远非当年可比。以每GB计的智能密度来看，特斯拉AI至少比当前其他任何系统高出一个数量级。不少网友也站在了马斯克一边，认为特斯拉的自动驾驶能力已经超越Waymo。也有更理性的分析指出，双方差异的根源在系统架构：Waymo采用的是模块化自动驾驶体系，高度依赖高精地图、激光雷达、传感器、5G网络以及远程人工确认。这种方案在正常情况下表现稳定，但一旦关键模块失效，系统就会迅速退回到安全策略，例如在停电时进入“变砖模式”。而特斯拉FSD走的是端到端神经网络路线：通过一个超大模型，直接将摄像头像素映射到转向和制动控制，以海量真实驾驶数据取代人工规则。这种方案在极端情况下更具适应性，但也对模型能力提出了更高要求。所以，现实依然是，Waymo在规模、合规和商业化进度上处于绝对领先；特斯拉押注的是FSD成熟后带来的指数级扩张能力。而随着亚马逊Zoox等玩家继续入场，北美Robotaxi赛道还远未定局。不过，可以确定的是，这将是一场长期、烧钱、且高度依赖技术路线选择的绞肉战场。One More Thing值得一提的是，在前段时间旧金山停电事件中，马斯克还贴脸开大嘲讽Waymo。特斯拉Robotaxi就没受到旧金山停电的影响。俗话说，趁你病，要你命，老马的这番拷打也足足给特斯拉吸了一波大粉，该贴点赞已超9.9万。不过，回到常态，理性分析来看，自动驾驶的桂冠最终将花落谁家，难有定论。但可以确定的是，随着技术不断成熟，汽车是否具备“自动驾驶”能力，不再仅仅从一项锦上添花的附加功能，而是会在真正左右消费者的购车决策。而在新版FSD实现实力口碑双丰收后，特斯拉似乎再次瞄准这一争议点，在微博暗暗发布了挑衅：将来无法实现自动驾驶的车就像……（大哥大）参考链接：[1]https://x.com/DrJimFan/status/2003593613918531891[2]https://www.cnbc.com/2025/12/16/waymo-amazon-zoox-tesla-robotaxi-expansion.html[3]https://medium.com/@akshay.x/teslas-ex-ai-chief-backed-waymo-elon-musk-pushed-back-9351f0397a53[4]https://x.com/Yuchenj_UW[5]https://www.tesla.com/support/fsd?utm_source=chatgpt.com[6]https://www.reddit.com/r/TeslaFSD/一键三连“点赞”“转发”“小心心”欢迎在评论区留下你的想法！—完— 点亮星标 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