甲骨文们的指引一个比一个炸裂，但历史泼了一盆冷水

华尔街见闻02-11

ChatGPT在2022年底把生成式AI推到大众视野后，投资端的变化更快：企业在AI硬件、数据中心上的投入力度，已经接近美国历史上几次最大的投资浪潮。市场随之抛出一堆漂亮的收入曲线，但问题也变得尖锐——这些预测到底有多大概率能实现，值不值得为此付出资本和时间成本？据追风交易台消息，摩根士丹利投资管理旗下Counterpoint Global的Michael J. Mauboussin在10日的...

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Mauboussin在10日的报告中直截了当地给出方法论：评估这类前瞻判断，应该“starting with an initial belief and updating that belief as new results appear”，也就是“贝叶斯公式”：“新结论 = 初始判断（先验概率） × 新证据带来的调整系数（似然比）”。\n\n沿着这套框架，报告把两个最受关注的预测放回历史分布里：OpenAI从2024年37亿美元收入到2029年1450亿美元（对应5年108%复合增速），以及甲骨文云业务从2025财年100亿美元到2030财年1660亿美元（5年75%复合增速）。结论相当不客气：在1950-2024年的美国上市公司样本里，这种体量起步的公司，没人做到过。\n更麻烦的是，AI基础设施不是“多买几台服务器”这么简单。数据中心建设本质是大工程，而大工程有自己的基准失败率：预算超支、工期延误、收益不达预期几乎是常态。报告还顺手把这轮密集的交易与“扩产宣言”放进竞争策略里解释：它们可能不只是为满足需求，也是在向对手发信号、试图威慑潜在进入者——但这种先发式押注本身就带着高风险。\n先把OpenAI的预测放进历史分布：108%复合增速在样本里是“空白”\n报告用的参照系很具体：挑出1950-2024年美国上市公司中，起始收入在20亿-50亿美元（按2024年美元口径）的一组公司，样本接近18900个“公司-期间”观察值。这个组别的5年收入复合增速均值只有7.0%，标准差10.6%。\nOpenAI的预测意味着：从2024年37亿美元到2029年1450亿美元，5年复合增速108%。报告的说法很硬——在过去四分之三个世纪里，没有上市公司做到过这种速度。即便用正态近似去描述，这也是接近9.5个标准差的结果，概率极低；而且历史增速分布本身并不服从正态，尾部更“肥”，但依旧改变不了“几乎不可见”的结论。\n\n一个细节很值得玩味：因为样本里“从未发生”，基准概率会变成0，贝叶斯公式本身就没法直接用。报告采取了常见的启发式处理（例如3/N、Laplace smoothing），得到的初始概率也仍然低于千分之一。\n证据确实在“抬概率”，但抬到哪一步，报告没有替你乐观\n报告也承认，基准概率不是铁律，世界会变。它给了两条能把OpenAI成功概率从“接近0”往上推的证据：\n\n扩散速度：ChatGPT用2个月达到1亿用户；对比之下，TikTok是9个月、Instagram是28个月、Facebook是4.5年；互联网达到1亿用户用了7年，手机16年，电话75年。即便考虑人口变化，这个速度仍属历史罕见。报告同时提醒：用户不等于收入，很多人并不付费。\n短期收入增速：OpenAI预计2025年收入约130亿美元，同比增速约250%。这远高于贯穿五年的平均复合增速。\n\n但报告紧接着把“乐观边界”钉住了：公司越大，增速的波动往往越小，想持续维持高增速会越来越难。并且，OpenAI还给出了2030年2000亿美元的收入预测——把窗口往后滚动，2025-2030年的5年复合增速仍有72.7%。\n报告再用起始收入100亿-150亿美元的参照类（约3700个观察值）去对照，结论仍是：没人做到过；就算把起始收入门槛放宽到至少65亿美元、样本扩大到16400多个观察值，还是没人做到过。\n增长不等于价值：现金流缺口与股权激励会把“高增长故事”拉回融资现实\n报告在这里换了一个更现实的提醒：增长本身不创造价值。它对“总可服务市场（TAM）”的定义也带了约束——不是“能卖多少”，而是“在创造股东价值的前提下，如果占到100%份额能有多少收入”；核心门槛是投资回报是否超过资本成本。\n在OpenAI案例里，报告直接把约束摆到台面上：\n\n2025年自由现金流据称为-90亿美元，并预计2026年为-170亿美元。在这种情况下，要维持“高速扩张+重投入”，几乎必然需要持续向外部投资者融资。\n员工薪酬中很大一部分是股权激励（SBC）：估算2025年SBC超过收入的45%，折算到员工层面约为每人每年150万美元的速度，而且是大型科技公司IPO前SBC发行强度的7倍。\n\n这些信息并不直接否定收入预测，但它把一个常被忽略的问题推到台前：就算收入增长兑现了，资本结构、融资条件和稀释成本，也可能决定“股东到底拿到什么”。\n甲骨文云的1660亿目标：签了单是优势，但交付与融资是硬约束\n甲骨文的叙事来自另一类证据：公司在2025年宣布了多笔数十亿美元级别的云基础设施合同，显著推高“Remaining Performance Obligations”（已签客户协议对应的未来收入）。管理层据此预测云业务收入从2025财年100亿美元增长到2030财年1660亿美元，对应5年75%复合增速。该云业务在2025财年约占甲骨文总收入574亿美元的17%。\n\n报告仍然先拿基准概率去压一遍：在过去75年里，起始收入达到100亿美元以上的公司，没有一家能在五年里跑出这种增速；哪怕把起始收入阈值降到56亿美元以上，仍然没有。\n它还给出一个更贴近甲骨文云体量的参照类：起始收入80亿-120亿美元，样本约4400个观察值，平均5年复合增速5.7%，标准差9.6%。报告也提醒，这是拿“公司业务部门”去对比“公司整体”，并非完全同口径。\n甲骨文的不同点在于：RPO规模确实可以让你在基准概率上做修正，但报告强调，修正不能只看订单，还得同时权衡——为增长配套的融资需求、对手方风险，以及基础设施落地可能出现的延迟。\nAI数据中心是典型“大工程”，而大工程的基准成功率并不站在你这边\nAI投入的“主战场”落在硬件和数据中心。报告提到，OpenAI与甲骨文同为“Stargate Project”的合作方，该项目预计到2029年在AI基础设施上投入最高可达5000亿美元。\n关键在于：AI数据中心和传统数据中心不同，硬件更贵，用电需求显著更高，也更依赖冷却系统。瓶颈很现实——电力接入、专用硬件供给。\n报告用Bent Flyvbjerg收集的16000个大型项目数据库做参照，结果几乎是“劝退级别”：\n\n47.9%的项目能在预算内完成；\n预算内且按时完成的只有8.5%；\n预算内、按时且实现预期收益的仅0.5%。\n\n\n它给出的启示很直接：别把“按计划落地”当默认选项。需要盯住电力、芯片和设备等关键瓶颈；同时，模块化设计相对更容易成功，但在AI需求快速增长、竞争者争抢领先身位的环境里，“慢想快干”并不容易执行。\n密集交易与扩产宣言，可能是一次“先发威慑”的竞争实验\n报告统计，OpenAI在2025年大约宣布了15笔与基础设施建设相关的交易。与此同时，Alphabet、Amazon、Microsoft等超大规模云厂商上调了资本开支预期，Anthropic、CoreWeave等也做出大额投入承诺。\n作者把这股热潮放回历史里对照：90年代末到00年代初的电信投资潮，最后留下的是产能过剩和破产案例。今天当然也有“需求还远没到天花板”的一面——报告引用的数据是，2025年下半年全球AI扩散率（使用过GenAI产品的人群占比）只有16%。\n真正有意思的是它对动机的猜测：这波动作可能部分源于一种战略信号——用大规模的产能承诺去锁定市场、威慑竞争者和潜在进入者。报告援引波特的“先发式扩产（preemptive strategy）”概念，同时也把风险写明白：这是在市场结局尚未明朗前，提前承诺巨额资源；如果没能吓退对手，可能引发更激烈的消耗战。更现实的分化是融资能力：初创AI公司需要不断外部输血，亚马逊、谷歌、Meta这类巨头则拥有更充裕的现金流，耐受度完全不同。通过2025年，资本还在供给，但报告明确说了：这件事会变。\n这份报告真正想让你做的事：把故事拆成概率，随数据改口\n报告反复强调的不是“看空AI”，而是把判断流程改成可更新的概率问题：先用基准概率给狂热设门槛，再用扩散速度、真实收入、工程进度、融资条件去一点点修正。它也强调自己不提供投资建议——但它提供了一个更难自欺的起点：当预测落在历史样本从未出现的区域，乐观本身就需要证据，而且需要持续的证据。","kind":"highlight","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"symbols":[],"gpt_button":0,"need_auth":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)","isDev":false,"isTTM":false,"tenantId":"TBCN","deviceId":"web-server-community-laohu8-v3","version":"4.36.2","shortVersion":"4.36.2","platform":"web","vendor":"web","appName":"laohu8","isIOS":false,"isAndroid":false,"isTiger":false,"isTHS":false,"isWeiXin":false,"isWeiXinMini":false,"isWeiBo":false,"isQQ":false,"isBaiduSwan":false,"isBaiduBox":false,"isDingTalk":false,"isToutiao":false,"isOnePlus":false,"isHuaWei":false,"isXiaomi":false,"isXiaomiWebView":false,"isOppo":false,"isVivo":false,"isSamsung":false,"isMobile":false},"href":"/m/news/2610588982","isCrawlerRequest":true}