“AI 2028危机”，究竟有多少已然发生

未尽研究02-24

进入2026年，进入马年，市场正弥漫着一种诡异的、前所未有的气氛。资本市场正在提前交易一场尚未真正到来的结构变化。从“一件大事正在发生”，到“2028年全球AI危机”，美国股市越来越容易被这些宏大叙事所牵引。华尔街怀疑，AI能力的自我递归提升，会先于制度与市场的调节能力，同时制造一次宏观经济的自我递归式的恶化。昨晚，独立研究机构Citrini用一篇假设写于2028年6月的备忘录，讲述了这样相互嵌套...

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happened","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"89988":0.6,"AMD":0.9,"HBBD.SI":0.6,"ALBmain":0.6,".DJI":1.85,"09988":0.9,"GOOGL":0.9,"GOOG":0.9,"BABA":0.9,"AIQ":1.82,"DIA":1.85},"content_text":"进入2026年，进入马年，市场正弥漫着一种诡异的、前所未有的气氛。资本市场正在提前交易一场尚未真正到来的结构变化。从“一件大事正在发生”，到“2028年全球AI危机”，美国股市越来越容易被这些宏大叙事所牵引。华尔街怀疑，AI能力的自我递归提升，会先于制度与市场的调节能力，同时制造一次宏观经济的自我递归式的恶化。昨晚，独立研究机构Citrini用一篇假设写于2028年6月的备忘录，讲述了这样相互嵌套的递归链条。当晚，美国再次崩盘，道指下跌800点，不仅包括前阵子就深跌的SaaS股与网络安全股，这次还包括黑石（Blackstone）、万事达（Mastercard）这样的金融大蓝筹。Citrini并带来没有太多新鲜的观点，很多都是ChatGPT刚出现时，经济学家就已经提出的担忧，以及一些AI大咖们制造的叙事。但它这次把悲剧展开的每一个环节都数据化、时间线化，详细推演了多米诺骨牌是如何依次倒下的，使其看起来更像一场正在展开的系统性风险：AI吃掉了软件，白领大量失业，中介经济瓦解，可选消费萎靡，私募信贷与抵押贷款违约率上升，而在税基收缩的背景下，财政政策也难以为继。这些危机叙事显得逼真，是因为它们并非从未来倒推，而是从当下延伸。现实已经出现了若干可被拼接的信号。“软件只是开场”正在变成一种共识。近期，Anthropic突破白领工业革命的积极尝试，让市场相信，那些支撑美国经济的高价值知识工作，不再被视为自动化的例外，正在接近系统性替代的拐点。围绕Anthropic的Claude Code所衍生的协作形态，市场第一次直面“AI吃掉软件”的可能性。过去几年，SaaS公司是资本市场的宠儿。它们将企业工具、流程与协作规则产品化，通过云端交付，以“席位”模式向企业收费。但是代理式的软件能自动化地实现这些功能，并且开始替代企业白领员工操作软件和相关工具。SaaS软件公司，行动快的，将与紧随AI原生企业一同用AI吃掉软件；行动慢的，将被吃掉，或者沦为智能体的基础设施。Claude Code如何突破白领工业革命2026/2/23  完整阅读 >昨晚，Claude Code宣布可协助现代化COBOL（通用商业语言）代码库后，围绕遗留系统维护与企业级IT服务的长期价值开始受到市场质疑。IBM股价暴跌13%。这意味着AI对于现有代码库的“清算”，可能会倒查到AI初生的1950年代。Anthropic并未将能力局限于编程场景，而是在加速向更多垂直行业扩展。随着智能体生态的形成，Claude Code的能力开始在不同工作流中迁移与泛化，并在真实业务环境中持续吸收“世界知识”。尽管其列举的医疗、法律、金融、教育、客服、物流等16个垂直行业，智能体的渗透率仍明显低于编程领域，但趋势方向已经明确。来自CB Insights的市场地图显示，Anthropic通过投资、合作与生态布局，正向企业价值链的多个下游环节延伸。在这种结构扩张之下，站在前沿模型厂商价值链下游，未必是安全的位置。“反身性循环”的逻辑是成立的，至少在能力层面已经显现。从近期Anthropic对AI智能体在实际工作流中的自主性（autonomy），以及人类与之协作的流畅性（fluency index）来看，大模型的自我递归式的改善，仍在继续。现在，用户让Claude Code不间断自动执行任务的时长已超过45分钟，几乎是三个月前的两倍。这不仅意味着模型能力增强，也意味着信任阈值正在上移。编程是AI能力“自我递归改善”的起点。Anthropic创始人达里奥·阿莫迪（Dario Amodei）与谷歌DeepMind创始人德米斯·哈萨比斯（Demis Hassabis），最近都谈到了“持续学习”的概念。阿莫迪的设想是，先开发擅长编码和AI研究的模型，然后用这些模型来生成下一代模型，并加速形成一个循环，从而提升模型开发速度。哈萨比斯要谨慎一点，认为仍需要数次范式突破。但无论如何，两种判断的分歧在节奏，而非方向；这一天最终都会到来。当这种能力提升进入企业端，另一种递归便随之出现：软件企业将裁员省下的钱继续投入AI工具，而AI能力提升又让下一轮裁员成为可能。回想一下，外语教育软件Duolingo是最积极拥抱AI的企业之一，从2021年开始就与OpenAI达成合作，也是OpenAI官网公布的首批GPT-4用例企业。它拿到了OpenAI万亿token消耗奖章，大幅减少人工内容，却也是市值跌幅最大的企业之一。当世界被token淹没，价值去哪里了2025/10/20  完整阅读 >“中介层变革”正在显露轮廓。去年，Google推出AP2，允许智能体之间进行直接支付与结算。这被视为智能体协作走向真实交易场景的早期尝试，也标志着从传统电子商务向“AI商务”过渡的可能路径。当交易可以在智能体之间完成，撮合与流量分发的价值位置便开始下移。如果结算工具与稳定币基础设施逐步成熟，智能体之间的MarketPlace可能绕开部分传统平台的中介环节。从电子商务到AI商务：谷歌发布AP2，以后智能体之间可以直接支付打赏了2025/09/17  完整阅读 >传统业务逻辑层正在被“agent tier”取代，其边际价值正被智能体吞噬。今年春节期间，阿里巴巴补贴AI下单，近2亿用户使用千问，实现一句话购买奶茶、订机票酒店、买电影票。这种交互方式，本质上将原本分散在电商、外卖与支付应用中的核心流程“插件化”，原本流经这些应用的流量，不再绕道，而是直接在千问App闭环。当注意力不再停留在应用界面，依赖流量分发与广告变现的商业模式，便面临结构性挑战。这往往需要最高决策者的拍板。也许正因为此，直到去年下半年，阿里巴巴才正式确立以千问为核心的集团级战略。就连因此而来的“token消耗”估算也是合理的。前述文章预测，到2027年3月，美国人均日均token消耗将达到40万（全年近1.5亿）。这甚至是一个偏保守的估计，受限于算力需求增长受到了算力供给约束的场景。让我们简单推算一下。去年10月，谷歌日均消耗43万亿tokens。当时，谷歌模型在OpenRouter市场占比25%。那么，当时全球相当于日均消耗170万亿tokens。在今年的CES上，黄仁勋预计全球token将每年增长5倍，那么，相当于2027年3月全球日均token消耗超过1600万亿tokens，即全球80亿人，每人每天消耗20万tokens。考虑到AI渗透率在全球并不均衡，届时，美国人日均消耗约40万tokens大致成立。事实上，在大型节庆或内容高峰期，token消耗呈现脉冲式放大并不意外。在2027年3月之前，人类社会已经面临AI春晚的冲击，也将面临AI世界杯的冲击。按照前述方法推断，在春节期间，全球日均token消耗已经超过了300万亿，其中来自字节跳动的或已在90万亿左右。视频生成与智能体经济，在推动算力需求爆发式增长的同时，也在倒逼算力基础设施建设加速，以及从现有基础设施中压榨出更多token。“就业市场动荡”已经是现实议题。几乎所有的实验室，都会承认AI会带来就业问题，只是程度不同而已。OpenAI创始人CEO奥特曼的观点是要建立UBI（全民基本收入）制度；Anthropic则在2025年4月建立了经济顾问委员会，DeepMind如今又开始招聘首席经济学家。准备后AGI时代，DeepMind在招聘首席经济学家 | 笔记2026/01/24  完整阅读 >这是一个狼来了的故事。尽管有人戏称，人工智能无处不在，唯独不在即将公布的宏观经济数据中。但就在这个月，美国国家经济研究局（NBER）在对美国、英国、德国和澳大利亚数千名最高管理层（C-suite）调查中发现，尽管高管与员工使用AI的时长大致相同（平均每周约1.8小时），但相比员工预计未来三年AI将提高生产率约0.9%，使其所在公司就业人数增加约0.5%，高管则预计同期生产率将提高1.4%，使所有企业就业减少0.7%。企业裁不裁员，最终还是得听高管的。“智能取代螺旋”并非纯粹假设。相关叙事推演的是，被智能体挤出市场的白领工作者流向蓝领岗位、低薪服务行业甚至零工经济，压低了工资，但自动驾驶等AI应用，正在后面追杀，蚕食这些市场。日前，在回应国会质询时，Waymo披露其在全球范围内拥有大约“在任何给定时间在线值班的”70名远程协助（remote assistance），包括事件响应团队，大约一半在美国（主要在亚利桑那和密歇根），另一半在菲律宾。目前，Waymo车队约有3000辆自动驾驶汽车，理论上1人负责40余辆。去年一季度时，小马智行曾披露1人负责20辆车，实现广州单车盈利转正，并预计到去年底提升为30辆。这意味着至少在驾驶及相关工作上，AI消灭了更多岗位，却没有创造足够的替代。不过，现在是2026年2月，不是2028年6月，“金丝雀还活着”。尽管当前资本市场押注，AI自我递归提升的速度，将系统性地快于经济与社会制度适应调整的速度，但是，企业家、就业者与监管层，都还有时间，及时建立新的均衡的框架。最终，这才能证明近期的股市暴跌，是金融资本在技术革命中的又一次过度定价。","kind":"news","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; 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