编辑：米奇 来源：财经会议圈
今年7月，长期唱空AI的知名科技行业评论人Ed Zitron近期发布1.5万字重磅文章《Let AI Burn》，抛出了一个迄今最具冲击力的判断：
真正的AI泡沫，本质上就是“OpenAI泡沫”。
以下是核心内容总结：
空头核心论断：OpenAI是“系统重要性机构”
Ed Zitron认为OpenAI是整个AI投资周期的“信用锚”——自ChatGPT问世以来，投资者对AI改变世界、GPU需求高增、大模型盈利的所有信仰都建立在OpenAI持续成长的前提上。一旦它倒下，冲击远超一家独角兽本身，类比2008年雷曼兄弟暴露金融体系杠杆脆弱性，OpenAI失败将终结AI狂热时代。
支撑论据：触目惊心的财务与商业模式缺陷
财务黑洞：援引所谓OpenAI审计财报数据，2025年营收130.7亿美元、总支出340亿美元、净亏损385亿美元（2024年营收37亿、亏50.9亿，亏损增速远超收入）；2026年Q1营收57亿、烧钱37亿，预计全年烧170亿（2025年为90亿），到2030年底累计消耗或超8520亿美元，离盈利越来越远。
商业模式两大硬伤（称“史上最大资本错配”）：
推理成本过高：用户提问持续消耗GPU、电力、服务器成本，大量低价/免费用户导致规模越大亏损越重；当前AI服务定价远低于实际成本（“1美元卖40美元的服务”），企业级收入跟不上成本增长，且不少企业已在削减AI支出。
资本开支远快于现金流：AI行业最大支出已从训练转向推理算力、GPU采购、数据中心建设，OpenAI 2026年仅算力支出预计超500亿美元，四大科技巨头2026年资本支出超7650亿美元；且AI行业70%营收本质是OpenAI/Anthropic的计算支出（风投→AI实验室→云厂商→英伟达的资金闭环），非真实健康需求。
雷曼时刻的传导逻辑
OpenAI崩溃不会突然发生，而是先融资变难→数据中心利用率下降→相关企业估值重估→传导至科技股市场；Oracle、CoreWeave等依赖AI基建需求的企业首当其冲。此外OpenAI、Anthropic、SpaceX的IPO若表现不佳，会引发流动性转移（基金接盘、投资者抛售其他股）的连锁反应
让 AI 行业自生自灭（中文全文）
作者：埃德・齐特龙（Ed Zitron）原文出处：Where’s Your Ed At
本周我发布了《软银黑粉全指南》，讲透了科技圈最疯狂赌徒的龌龊往事。当初几笔侥幸的早期投资让它风光无限，如今却为 AI 泡沫史上规模最大、也最解气的崩盘埋下伏笔。本周五，我还会深度剖析存储芯片行业，解释为什么现在配一台高性能游戏 PC 贵到普通人难以承受。
订阅我的付费专栏性价比极高，也正是靠付费读者的支持，我才能每周产出这篇万字级、深度调研的免费长文。
不要救助、不要补贴、不要特殊优待、不要税收减免、不要《芯片与科学法案》倾斜政策，更不能设立主权财富基金托底 AI 产业。是时候让整个 AI 行业自食恶果了 —— 它对待社会的方式，本就配不上任何庇护。这个行业一无是处，完全是山穷水尽的硅谷编造出来的骗局，凭空催生了数万亿美元的舆论造势，还埋下多场本可避免的金融危机；无论如何，我们都不该出手保全它。
只要你听到有人提起 “行业救助”“大而不能倒” 或是 “主权财富基金托市”，就要明白：这是业内人士在想方设法营造 “行业不能倒下” 的假象。但事实上，这里每一家企业都和普通初创公司一样脆弱不堪。
另外，媒体乃至全社会都轻易接受了 “泡沫破裂后政府会出手救助” 的预设，只因 2008 年金融危机的始作俑者最后全都逃脱追责。但我必须厘清：AI 产业和金融业有着本质区别。它对国民经济并非刚需，所谓行业体量，完全靠铺天盖地的营销炒作撑起来。
这是一群失败者堆出来的泡沫。它之所以能越吹越大，无非是硅谷、主流媒体和彻底扭曲的股市达成了默契 —— 股市纵容圈钱与循环融资。今年一季度，OpenAI 营收 57 亿美元，Anthropic 接近 50 亿美元，可这些收入大多来自不计成本消耗 AI 算力代币的企业客户，而眼下所有企业都在疯狂削减相关开支。
生成式人工智能永远实现不了通用人工智能（AGI），它能做到的事，也和大众认知里的人工智能相去甚远。它没有自主行动能力，谈不上任何 “智能”，不存在自我意识与真正的知识储备。无论给大模型套上多少层调度框架、编写多少配套脚本，按照 OpenAI 自己的官方说法，它在数学层面注定会产生事实幻觉。据我估算，全行业至少七成收入都只是 OpenAI 与 Anthropic 消耗算力产生的流水。而这两家企业亏损极其严重，也就是说整个 AI 产业的本质，无非是风投把资金输送给云厂商，云厂商再把钱流向英伟达或是数据中心基建。
倘若这套软件真有实打实的价值，它完全可以自给自足，根本不需要循环融资和个人崇拜式宣传来续命。如果它真的独一无二，也不会有大批狂热信徒，但凡有人质疑这套产品，就群起而攻之。人类历史上，从来没有哪一款工具或商品，需要靠如此歇斯底里、排他性极强的宣传去兜售，最后证明不是一场骗局。不少人对大语言模型、以及背后开发公司产生了病态的执念，驱动他们维护 AI 产业的不是任何成熟技术或 AGI 落地的实证，只是这种扭曲的情感依附。
这套软件本身自带阴暗属性：一方面，它会放大人性中的恶意；另一方面，背后运营企业的底色也不堪入目。每隔几周，Anthropic 就会推出一批新发言人，一个个神情麻木、毫无灵气，说话越来越怪异、充满邪教式狂热，与现实世界完全脱节。硅谷自诩无神论，但 Anthropic 内部以及粉丝群体中弥漫着令人不安的盲从氛围。你可以想象一款游戏最极端、最偏执的饭圈，再叠加金融投机、割韭菜、青春期式内斗，所有人只为一款线上软件疯狂。
拜托各位，现实里没人关心什么 “智能循环”，没人钻研分词、词元化。你在街上随便拉一个路人说 “推理算力”，对方只会觉得你该去看精神科医生。没人在乎 OpenClaw 这类小众项目。清醒一点，多出门走走，你现在的样子和疯子无异。你父母知道你注册了几十个 Claude 高级账号吗？这种沉迷早已病态。
言归正传，AI 之所以能在经济中占据一席之地，根源只有一个：微软、谷歌、Meta、亚马逊计划 2026 年投入超 7650 亿美元资本开支，2027 年再砸一万多亿。它们再也拿不出新的高速增长赛道，即便生成式 AI 至今没能创造具备规模、可持续的营收（更别说盈利）。我上周在 CNBC 节目上也点明了这点：这些巨头从未单独披露纯粹的 AI 业务收入。
谷歌拿不出第二个谷歌搜索，微软造不出下一代 Office，Meta 复刻不了 Facebook，亚马逊也没有第二个 AWS。正因如此，它们要全社会默认 AI 是划时代机遇，却从不拿出实际营收数据佐证，只能靠疯狂砸钱基建制造假象。可如果剔除 OpenAI 和 Anthropic 两家企业（头部 AI 公司 89% 的流水都来自它们的算力采购），全球 AI 行业年营收最多也就 200 亿美元。
行业从业者总把一句话挂嘴边：“现在还处于早期阶段”，拿当年互联网泡沫类比，只为说服大众接纳 AI，或是把人类史上规模空前的资本错配包装成 “搭建有用的数字基建”。
别再强行把当下 AI 泡沫对标互联网泡沫
我直白说：AI 显卡只适配生成式 AI，几乎没有其他用途。大语言模型每一次所谓 “创新”，都只是靠砸数十亿资金堆人力、堆算力换来。全行业顶尖人才、全部媒体流量、绝大多数投融资，全都押注在单一赛道，最后产出的大模型成本远高于人力，实用价值却大幅不及真人。
AI 从业者总爱空谈虚无缥缈的未来设想，只因把产品落地后对比其天价成本，实际效果平庸到不值一提。仅 2026 年，Anthropic 和 OpenAI 融资总额（若全部交割完成）就超 3000 亿美元，占据全球绝大多数 AI 算力资源。他们只能不断画远期大饼，因为目前落地的所有成果，连其投入成本的零头都无法证明合理。
一旦 AI 泡沫破裂，如今搭建的海量算力基建几乎没有复用价值。我在付费专栏里写过，这次泡沫的后果远比互联网泡沫严重：显卡和光纤完全不是一回事。显卡运行耗电惊人，数据中心运维成本居高不下，适用场景极其单一，且高度集中。光纤泡沫破裂后可以大范围二次利用、低价折价清算，但显卡做不到。普通爱好者无力承接，持续运营成本居高不下，烂尾的数据中心也很难完工盘活。
互联网泡沫时期搭建光纤，当年有一套广为流传的谎言：网络流量每 90 天翻一番。各大券商研报、企业财报电话会、投资人路演、所有科技媒体都在重复这个说法，但这套数据完全是捏造的。AT&T 网络研究员安德鲁・奥德里兹科核查真实流量数据后发现，美国主干网流量实际一年才翻一倍 —— 增速确实可观，但远达不到分析师鼓吹的离谱数字。运营商靠花式财务造假掩盖数据缺口，手段堪比中世纪炼金术士：出售数十年光纤使用权，一次性全额计入营收；运营商之间互相交换带宽，虚增账面收入。
另外，互联网泡沫时期行业确实处于起步阶段，网速极差。2000 年，仅有 52% 美国成年人使用互联网，2003 年这一比例也只涨到 61%。世界银行数据显示，2005 年全球网民仅占总人口 16%，到 2024 年才提升至 71%。当年上网靠 56K 拨号，按分钟计费，速度极慢；2000 至 2002 年，美国平均网速最高仅 400 千比特 / 秒，换算成下载速度约 50KB/s。如今美国平均网速超 200 兆比特 / 秒，下载速度可达 25MB/s。泡沫破裂后，光纤依旧保留极高残值，存活下来的运营商持续受益。比如 2004 至 2010 年，威瑞森斥资 230 亿美元铺设家庭光纤宽带，依托的正是泡沫时期遗留的光纤资源。
反观生成式 AI，如今铺天盖地渗透所有场景：几乎每一款 App 都强制内置 AI 功能，脸书、谷歌、微软所有账号默认开启 AI，2023 年以来所有主流媒体反复报道 AI 概念。OpenAI、Anthropic 嘴上说着算力不足，可 “扩建数据中心” 除了托举英伟达销量、给云厂商提供花钱渠道，看不出任何实际价值。算力短缺根本没有阻碍大众使用 AI 产品，也没有拦住创业公司发布新产品。没人能说清新建海量机房到底要承载什么刚需，只能含糊解释 “给 OpenAI、Anthropic 消耗算力”。
Anthropic 所谓算力紧缺，丝毫没有耽误它训练、发布 Mythos、Fable 系列大模型；它从 SpaceX 采购数百兆瓦算力后，最大的新闻只是上调用户额度，让客户每月花 200 美元，就能消耗价值 8000 美元的代币。数据中心建设缓慢，完全没有限制任何一家 AI 企业发展。扩建算力的全部逻辑，不过是 “造更多算力，等着客户花钱消耗”，完全没有清晰的市场刚需支撑。
英伟达宣称 2027 年底显卡销售额将突破一万亿美元，为承接这笔天量需求，行业要投入至少 4350 亿美元搭建算力基建。我们到底需要多大规模的配套设施？按英伟达规划，到 2027 年末要售出承载 30 吉瓦以上算力的显卡，配套数据中心总供电容量需要达到 40 吉瓦（电源使用效率 PUE 取 1.35）。仅机房内 AI 算力硬件（不含制冷、输电损耗）每兆瓦造价 1200 万美元，仅 IT 硬件投入就高达 4350 亿美元，土地、土建、人力、输电、制冷等成本还要另算。
OpenAI 预估 2026 年算力开销达 500 亿美元，Anthropic 投入规模与之相近。除微软、谷歌、亚马逊为两家企业兜底、租赁算力外，仅有 Meta 拥有可观算力投入（旗下 Nebius、CoreWeave 承接算力业务）。而彭博社消息显示，Meta 计划对外出售闲置算力，这又是一大佐证：市场根本不存在大规模真实刚需。
追捧 AI 的业内人士会辩解 “自建算力是为了发债融资”，但这套说辞站不住脚。当下全球三分之二风投资金涌向 AI 赛道，云厂商手握数千亿未履约算力订单，真相却不堪入目：云厂商五成待履约订单来自 OpenAI 与 Anthropic。剔除这两家企业，微软算力订单同比增长停滞，亚马逊增速仅 20%；谷歌数据虽更杂乱，但整体趋势完全一致。等到市场不再追捧 AI 战略、没人再空谈 “自主可控 AI” 时，所有人都会看清真相：AI 真实市场需求极其薄弱。
目前没有可靠证据证明，推理算力服务能够盈利。也就是说，即便开源大模型熬过前沿实验室泡沫，其单位经济模型也存在根本性缺陷。当下所谓 AI 需求，本质是舆论裹挟、软件强制捆绑 AI 功能逼出来的伪需求。确实有少量用户愿意付费使用 ChatGPT、Claude，但绝大多数算力消耗来自免费功能，或是售价极低、严重亏本的套餐。用户每月花 20、200 美元订阅服务，其消耗算力的真实成本远超售价。借用科里・多克托罗的话总结：行业在用价值 40 美元的算力，一美元低价出售。这根本算不上健康商业，更谈不上原生市场需求。
AI 鼓吹者声称扩大规模就能摊薄成本，但现实恰恰相反：规模扩张从未降低 AI 使用成本。新一代显卡、博通自研芯片、亚马逊 Trainium、谷歌 TPU，全都没能实现降价。就算未来成本奇迹式下跌，市面上已经上架数万机柜的 H100、H200、B100、B200、B300、AMD 显卡，又该如何处置？
每次刷到有人在社交平台说 “行业尚早，大部分人还没用过智能体”，我都忍不住想反驳。智能体概念早已充斥所有媒体，但凡一点基础网页检索、代码生成功能，从业者都强行包装成 “智能体”。大众对 AI 兴致平平，核心原因很简单：现有产品做不到大众期待的自主智能 —— 无需大量人工指令，自动完成各类事务；所有人都清楚模型会编造虚假信息；数据中心消耗巨量电力、水资源，还能拿到大额税收补贴，背后掌权的却是凯文・奥利里这类投机富豪，或是奥特曼、阿莫迪这类脱离底层的硅谷精英。
那些天天焦虑 “中国 AI 会超越美国” 的人，活在孩童式幻想里。先说事实：Anthropic 自己都承认，廉价开源模型（包括自家 Claude Haiku 4.5、月之暗面 Kimi K2.7），在安全漏洞检测上效果和旗舰 Fable 模型不相上下。所谓大国科技竞争论调，只是游说政府发放补贴、减免税收、廉价出让土地给数据中心开发商与地产投机商的工具。AI 机房造价高昂，泡沫破裂后，企业想筹资完工、盘活资产会难如登天。
我明白所有人都期盼泡沫崩盘后能迎来圆满结局，习惯套用熟悉的历史案例（哪怕纳斯达克暴跌 77%），只因互联网泡沫后确实诞生了一批优质企业。有人拿优步、AWS 举例，证明 AI 行业最终能盈利，但两类类比完全不成立。记者、券商分析师刻意忽略所有风险信号，只会重复 “这就像当年的优步”“对标 AWS”。2003 至 2015 年，亚马逊为 AWS 累计资本开支 297 亿美元，和当下涌向生成式 AI 的万亿投入完全不在一个量级；而且早在大模型问世前，云服务器托管就已经拥有实打实、全企业层面的刚性需求。
AI 产业绝非 “大而不能倒”，政府也无力救助
OpenAI 掌舵人山姆・奥特曼提议，把公司 5% 股权划拨给美国政府，这笔股权估值约 4200 亿美元。奥特曼与 OpenAI 其他高管还建议，美国头部 AI 企业各拿出 5% 股权，组建类似阿拉斯加永久基金的国有载体。可 OpenAI 预估到 2030 年末累计亏损将达 8520 亿美元，区区 5% 国有股权，只能延缓崩盘，无法改变最终结局。
支撑这场泡沫的，是四大相互交织、无法持续的危机：
- 数据中心投机泡沫
：市场盲目扩建 AI 显卡机房，预期每年能产生 4500 亿美元以上机房收入。可剔除两家靠风投输血的头部实验室，全行业原生刚需仅有几十亿美元规模。
- AI 初创公司泡沫
：绝大多数 AI 初创企业估值虚高，看不到被收购、上市的可行路径。所有创业公司都依赖采购 OpenAI、Anthropic 代币，现金流消耗速度极快，吞噬全球绝大多数风投资金。
- 私人信贷泡沫
：资管机构把万亿养老金、保险资金投入亏损、未完工的数据中心建设项目。
- 半导体泡沫
：数据中心催生的虚假需求填满芯片供应链，推高内存、存储价格，所有消费、企业电子产品涨价，连机房自用硬件成本也同步上涨，形成恶性循环。短短 10 个月，千兆瓦级数据中心整体造价从 500 亿翻倍至 1000 亿美元。
对比 2008 年金融危机，就能理解 AI 产业不存在系统性风险。当年若 AIG 破产，全球数十亿民众储蓄、养老账户、市政基金、保险保单会全部清零；持有 AIG 货币基金的普通投资者会血本无归。当年救助方案中，美联储推出一级交易商信贷工具、定期证券借贷工具，每个交易日向金融机构注入上千亿流动性，才避免市场彻底停摆。
反观 OpenAI 与 Anthropic，连同整个生成式 AI 行业，对宏观经济无系统影响。它们只是支撑美股 “七大巨头” 估值的符号，抛开 2026 年约 7500 亿至一万亿算力开销、600 亿合计营收，对实体经济影响微乎其微。剥离这两家企业，全球剩余 AI 企业年收入几乎可以忽略不计。
就算政府出手救助，也没有明确救助标的。除非无限期注入公共资金，等企业摸索出盈利模式 —— 本质等同于永久兜底。两家头部实验室没有巨额表内债务；阿莫迪旗下 Anthropic 价值 350 亿美元的 TPU 硬件采购订单，有阿波罗全球管理、博通兜底。它们的股权价值只和风投基金挂钩：一旦无法上市，对应基金整期收益率将全面崩盘。
专门聊聊软银
唯一深度绑定 OpenAI、存在系统性风险的大型企业，只有软银。我在《软银黑粉全指南》中详细说明：软银押上整个公司未来，为奥特曼无休止的算力烧钱提供超 400 亿美元短期过桥贷款。如果 OpenAI 无法按虚高的私募估值上市，软银将遭遇致命流动性危机。
即便软银出现危机，风险也远不及当年全球金融崩溃。但软银是日本股市核心上市公司，最大股东是规模 1.6 万亿美元的日本政府养老金 GPIF，后续或许能拿到日本政府定向扶持。但这只是单一区域企业风险，和生成式 AI 产业本身无关。
除非到 2030 年 AI 算力原生商业需求暴涨几十上百倍，覆盖全球软件行业 7790 亿美元年总收入，否则泡沫崩盘带来的大规模损失无可避免。
一旦云厂商大幅削减资本开支，英伟达显卡需求会瞬间蒸发；随之崩盘的是代工 AI 服务器的台湾 ODM 厂商；内存、存储芯片企业收入暴跌，整条科技硬件供应链陷入长期萧条。这一切的源头，只是一群只会招人、裁员、砸钱在未经验证软件上的行业决策者。
我反复强调：投资者、政策制定者混淆了两件事 —— 靠举债、机房投机、巨头寻求新增长故事催生的巨额资本开支，不等于多元、可持续的真实商业需求。企业估值完全靠市场情绪支撑，没有扎实的单位营收托底。一旦市场预期全面转向下行，股价没有任何基本面支撑。
补充私人信贷风险：我极度担忧规模数万亿美元、流动性极差的浮动利率私人信贷市场。目前无法统计它在 AI 泡沫中的完整敞口，但数百亿养老金已经投入烂尾、无盈利前景的数据中心项目。公立养老金法规禁止直接重仓亏损 AI 基建企业，可监管漏洞让它们通过私人信贷基金间接完成这场豪赌。
数千家 AI 初创企业估值暴跌，联邦政府根本无力全面兜底。除非美国国会划拨数千亿纳税人资金，纯粹收购毫无价值的创业公司股权，只为稳住风投基金账面收益。如此大规模救助法案，需要参众两院同时通过，政治层面完全行不通：进步派选民早已厌倦科技巨头无休止拿补贴，保守派选民一贯主张财政负责、维护工薪阶层纳税人利益。
别忘了，2008 年首轮银行救助法案首轮投票直接未通过，两党议员反对与支持人数各占一半。当时全美金融体系正在实时崩塌，才勉强推动后续救助。AI 产业不存在同等级别、迫在眉睫的系统性危机，不可能催生两党快速达成共识的紧急法案。
单独看数据中心泡沫：政府向来放任未完工、废弃工业资产闲置多年。2008 年四季度，全美 11% 住宅空置，计入度假房后空置率达 15%。土地本身具备残值，哪怕没有建起堆满亏损显卡的巨型机房。政府没有任何政策、经济动机出手救助，也绝不会出台专项法案。金融危机后数千家建筑企业直接破产，2007 至 2012 年美国建筑公司总量直接腰斩。
有人会辩称，未来总统会出台定向科技补贴、专项纾困政策，但这种空谈算不上严谨金融分析。如果所有对 AI 泡沫风险的反驳，都只模糊揣测政坛腐败，那只是危言耸听，而非客观基本面分析。
最关键一点：泡沫破裂后，大型科技巨头短期不会彻底垮台。英伟达大概率丢掉全球市值第一宝座，七大科技企业市值大幅缩水；除非出现极端恶性财务操作，微软、谷歌、Meta、亚马逊最多做数百亿资产减值；若查实英伟达违规向中国输送高端显卡，还可能面临 SEC 监管处罚。
但这不代表散户投资者、科技从业者、芯片供应链工人、养老金持有人、普通民众不会承受巨大损失。泡沫破裂后，AI 行业大规模裁员、纸面财富蒸发数万亿美元、民用电子产品涨价、私人信贷基金连锁亏损，会让和硅谷投机圈层毫无关联的普通人广泛蒙受经济损失。
这也是我写下本文核心观点的原因。
泡沫来临时，放任 AI 行业自生自灭
我重申立场：不要救助、不要补贴、不要特殊优待、不要税收减免、不要《芯片法案》定向倾斜，不要设立主权财富基金托举生成式 AI 产业。是时候让整个 AI 行业自食恶果 —— 它对待全社会的方式，不配得到一丝庇护。如果这套糟糕、无法盈利的商业模式脱离外部持续输血就难以为继，这些企业必须独立承担后果，体面破产。
各国政府长久以来对科技行业一味退让，被全球顶级富豪集体蒙蔽，误以为奥特曼、阿莫迪正在打造划时代产品，可实际上，他们只是做出了人类史上盈利能力最差的大众软件。
我们不需要所谓 “自主 AI 国家战略”，不需要 AI 主权财富基金，更不必执着 “美国领跑大模型赛道”——ChatGPT、Claude 背后的大语言模型，是人类史上宣传最夸大、营销最具欺骗性的软件之一。
就算大模型只能作为小众办公工具，也无关紧要。真正的问题在于：AI 行业索取无限土地、资金、稀缺自然资源，只为持续推进一套永远亏损、长期看不到盈利路径的技术。它能出圈，只是所有科技企业抱团打造的转移视线工具，掩盖一个残酷真相：行业再也拿不出能驱动增长、颠覆消费与企业服务的全新产品。大模型能实现的一切，都配不上万亿级资本投入。
这场泡沫能膨胀至今，离不开被资本俘获的财经、科技媒体：媒体刻意夸大模型能力，对事实失真、经济崩盘隐患轻描淡写。大批记者、分析师、评论人轻易被富豪创始人蛊惑，轻信他们在打造有自我意识的人工智能。等到市场万亿市值灰飞烟灭，这群媒体从业者必须承担鼓吹投机狂热的责任。2022 年末以来绝大多数 AI 报道，本质是服务顶级富豪、吹起灾难性资产泡沫的宣传工具，最终全球数亿普通人将长期承受经济损失；哪怕核心公司彻底倒闭，奥特曼、阿莫迪依旧稳坐亿万富豪席位。
泡沫降临之时，必须放任整个 AI 行业崩盘，完整承受市场出清。生成式 AI 已经拿到过多资金、媒体曝光、政策优待与地球稀缺资源；如果脱离风投持续输血、媒体无脑吹捧就无法存活，它完全不配社会保护，理应直面普通人经商失败时要承受的冰冷市场规则。
不存在神奇手段挽救这些商业模式崩坏的企业。给 OpenAI、Anthropic 划拨 4200 亿公共资金，改变不了其底层单位成本失衡的硬伤，也凭空造不出英伟达 2027 年前显卡销售所需的 40000 亿年度原生商业收入。
这群行业掌舵人不是在打造普惠变革未来，而是创造新机制固化财富分化，给微软、谷歌、亚马逊、Meta 找新借口扩大 recurring 收入，借 “创新” 之名集中全球算力基础设施。
如果政策制定者读到这篇文章，请认清：你们被 AI 行业游说团体系统性欺骗了。他们刻意渲染自身经济不可或缺，只为泡沫破裂后拿到政府救助，或是说服纳税人出资，在各州修建免税数据中心园区。他们研发的大语言模型架构，永远兑现不了自主通用人工智能的数十年承诺。
我不幻想泡沫始作俑者会承担个人法律责任，但崩盘后出台监管、政策改革时，必须追责到底：山姆・奥特曼、达里奥・阿莫迪、萨提亚・纳德拉、桑达尔・皮查伊、安迪・贾西、黄仁勋、马克・扎克伯格，以及所有刻意制造全民 AI 共识、埋下下一场全球金融危机隐患的高管。
科技行业不完成深层结构性改革，硅谷永远只会制造靠共识炒作的泡沫，产出巩固现有财富分层的工具。
因此，但凡政客、说客、企业高管暗示定向救助 AI 行业，直接拒绝；他们索要新税收减免、产业补贴的诉求一概无视。要求政策制定者冷静推演：如果行业对生成式 AI 的全部核心假设全部错误，长期经济代价是什么。AI 热潮落幕之后，我们必须完整复盘整场崩盘，杜绝同类投机狂热重演：查清每一家造势媒体、每一支跟风风投、每一位夸大宣传的企业高管与网红，如何联手编造大模型改变世界的虚假叙事，制造全民投机。
历史上每一轮大型资产泡沫，尘埃落定后风险制造者都极少被追责。我担忧本次崩盘带来的经济冲击会广泛波及普通家庭。我们必须尽全力完整复盘泡沫起源，落地长效监管机制杜绝历史重演，这意味着全社会要直面几个沉重议题：缺乏约束的私人金融体系、被资本裹挟的主流媒体、科技创新的投融资、估值、并购、补贴规则。
这套清算同样适用于网络上狂热的 AI 信徒。数百万网民形成极端排外心态，但凡有人不把商业科技公司的营销话术当成客观科学真理，就恶语相向。科技圈层里这种邪教式盲从，是根深蒂固的文化弊病，必须彻底根除。
接下来的市场重置无可避免，AI 泡沫落幕会引发全科技行业重估，给依附华尔街资本、无视大众福祉的硅谷文化一记必要的现实警钟。行业内个人崇拜文化根本不在乎普通劳动者，他们崇拜富豪精英，幻想活在顶层把控的分层社会。
我绝不接受他们这种狭隘、利己的未来叙事，更不承认这是人类唯一归宿。
几周前我写过一段话：舆论把 AI 泡沫包装成人类无可避免的科技未来，本质却是中期硅谷昂贵又漫长的落幕。只有一个完全被纸面财富、空洞价值创造主导的科技行业，才会容忍万亿资本浪费在一套理论、落地均无实证的技术上；也只有思想空洞、资本成瘾的硅谷圈层，会轻易被阿莫迪、奥特曼这类擅长煽动人心的投机者收割。
AI 热潮必须落幕，所有亏损 AI 企业，应当在无公共资金兜底的前提下完整出清。
让 AI 行业自生自灭。
Let AI Burn
作者：Ed Zitron发布时间：2026 年 7 月 7 日原文链接：https://www.wheresyoured.at/let-ai-burn/阅读时长：29 分钟（约 1.5 万字）配乐：Mastodon — Streambreather
全文
This week, I published the Hater’s Guide to Softbank — a sordid tale of tech’s most degenerate gambler, who, thanks to a couple of early lucky wins, has managed to set the foundations for the AI bubble’s biggest (and possibly most gratifying) downfall. And, on Friday, I’m going to take a deep dive into the memory industry — and the reason why you can’t afford a new gaming PC.
Subscribing to premium is both great value and makes it possible to write these large, deeply-researched free pieces every week.
No bailouts, no handouts, no special treatment, no tax breaks, no CHIPS act, and no sovereign wealth fund. It is time to tell the AI industry to go fuck itself, because it’s effectively done the same to the rest of society. This industry is unworthy — a sham conjured up by a tech industry that’s run out of ideas, a trillion-dollars’ worth of manufactured consent and entirely-avoidable financial crises — and should not be protected under any circumstance.
Every single time you hear somebody discuss “bailout” or “too big to fail” or “sovereign wealth funds,” know that this is the industry, on some level, attempting to create the air that it cannot die, when in fact every one of these companies is just as weak and brittle as any other startup.
I also think that the media — and the world at large — is too ready to accept the prospect of a bailout after watching those who drove the world into a ditch in 2008 escape blame, and I must be clear: the AI industry is very different to the financial industry. It is inessential to the economy, and its relevance is only as large as the hype campaign that sits behind it.
This is an industry of losers that has inflated only because of the joint manufactured consent of Silicon Valley, the mainstream media, and an enshittified stock market that rewards grifting and circular financing. OpenAI had $5.7 billion and Anthropic a little under $5 billion in the first quarter of this year — and those revenues mostly came from companies that were burning AI tokens at a horrendous rate because they’d just been forced to pay the actual cost of AI — and now everybody’s pulling back on that spend.
Generative AI will not bring us AGI, nor does it do much of what we associate with artificial intelligence. It is not autonomous. It is not “intelligent.” It does not have thoughts, or “knowledge,” and no matter how many layers of harnesses and scripts you put on top of it, it is still (per OpenAI) mathematically certain to hallucinate. I estimate that at least 70% of the entire AI industry’s revenues are made up of OpenAI and Anthropic’s compute spend, and as both companies are horrendously unprofitable, this means that the AI industry is, for the most part, venture capitalists funnelling money to hyperscalers so that they can funnel that money to NVIDIA or data center capex.
If this software were worthy, it would stand on its own two feet. It wouldn’t need circular financing and a cult of personality to prop it up, either. If it were truly special, there wouldn’t need to be an army of crazed acolytes that attack you for not pledging yourself to the graveyard smash. There has never been a tool or product in history sold with such hysteria and aggressive monocultural force that has ever turned out to be anything more than a grift. Some people have developed unhealthy relationships with large language models (LLMs) and the companies that make them, and that, not any certainty or proof of Artificial General Intelligence (AGI), is what motivates them.
This software is uniquely dark, both in what it unlocks in some people through its use and in the sense of the entities that sell it. Some people are in genuine awe of each of the rotation of clammy, soulless pod-people that saunter out of Anthropic every few weeks. Each one sounds a little weirder, more cultish, more disconnected from the real world. Silicon Valley may believe itself atheistic, but Anthropic has a worrying sense of fanaticism, both in the people that work there and its fanbase. Imagine the absolute worst fanbase of a video game possible, and then add layers of financialization, grifting and high school drama laced with pseudo-religious attachment. All for a fucking app!
Please, people. Nobody in the real world cares about “loops.” Nobody is thinking about tokenization. If you said inference to a guy on the street they’d take you to see a doctor. Nobody gives a shit. They don’t know what OpenClaw is either. Grow up. Go outside. You sound like a lunatic. Does your mother know how many Claude 20x accounts you have? It’s obsessive!
Anyway, the only reason that AI has any presence in our economy is that Microsoft, Google, Meta, and Amazon are intent on spending more than $765 billion in capital expenditures in 2026 and a trillion more in 2027 because they have no other hypergrowth ideas, even though generative AI has yet to show any real potential as something that can drive meaningful revenues (let alone profits), as evidenced by the fact that none of these companies break out their actual AI revenues, a point I made on CNBC late last week.
Google does not have the next Google Search, Microsoft does not have the next Microsoft Office, Meta does not have the next Facebook, and Amazon does not have the new AWS. That’s why they need you to believe that AI is a big deal without them ever having to prove why outside of capital expenditures. They want you to assume that all this money can’t be wrong, even though when you remove OpenAI and Anthropic (who represent 89% of the revenues of the largest AI companies) the AI industry is, at best, pulling in $20 billion in annual revenue.
And lord do they want you to say “it’s early,” and that it’s just like the Dot Com Bubble, all so that you’ll either accept AI as your lord and savior or, alternatively, help justify one of the largest misallocations of capital in history as “building useful infrastructure.”
Stop Pretending This AI Is Like The Dot Com Bubble
Newsflash! AI GPUs are useful for generative AI and not much else. Every “innovation” in LLMs has only been made possible by throwing billions of dollars at the problem either in headcount or compute costs — every ounce of talent in the tech industry, every bit of media attention, every dollar of capital expenditures, all focused on one industry that has successfully created LLMs that are more expensive and significantly less useful than human beings.
The reason every AI person speaks in pie-in-the-sky hypotheticals is that the actual outcomes are decidedly mediocre when you compare them to their ruinous costs. Anthropic and OpenAI raised (assuming the rounds completely close) over $300 billion in 2026 alone, and take up the vast majority of available AI compute. They need you to speak in the future tense, because nothing — absolutely nothing — about what’s been created so far justifies even a fraction of its financial and infrastructural cost.
When the AI bubble bursts, none of this infrastructure will be particularly useful. As I said in my premium about how this is worse than the Dot Com Bubble, GPUs are not fiber optic cable. They cost vastly more power to run, carry far higher ongoing operational expenses (To Power And Run The Data Centers), have significantly less utility, and are significantly more centralized. Unlike fiber, they cannot be repurposed broadly, liquidated cheaply, or auctioned at a steep discount by creditors. These are not going to be useful for hobbyists, nor will they be cheaper to run, nor will incomplete data centers be cheaper to finish.
The dot-com bubble’s infrastructure buildout was justified by another powerful myth—that internet traffic was doubling every 90 days. The claim spread through analyst reports, earnings calls, investor roadshows, and every tech media outlet alive. But the mathematics were fiction. Network researchers like Andrew Odlyzko (at AT&T), looking at actual traffic data, found that U.S. backbone traffic was doubling roughly once a year—rapid growth, but nothing close to the wild claims analysts pushed. Carriers buried the discrepancy under layers of creative accounting that would have impressed medieval alchemists. They sold “indefeasible rights of use”—essentially decades-long leases on fiber capacity—and booked the entire value immediately as revenue. They engaged in elaborate “capacity swaps” between carriers to inflate top-line numbers.
We were also fairly early, and internet speeds were atrocious. In 2000, only 52% of American adults were using the internet, and by 2003, that number had only increased to 61%. Per the World Bank, in 2005 only 16% of the world used the internet, and in 2024, that number had increased to 71%. When the internet was connected to via a 56k modem, access was charged by-the-minute, and obviously much slower. Back in 2000, 2001, or 2002, the average US internet speed was, at best, 400 Kilobits/s, or roughly 50 kilobytes a second, compared to the average US internet speed of over 200 Megabits per second, or 25 megabytes a second, today. Fiber optic cable retained enormous residual value after the bubble burst, both for the operators that survived and the providers. Verizon spent $23 billion on bringing FiOS to people’s homes between 2004 and 2010, for example, building on that leftover fiber.
Generative AI, on the other hand, is fucking everywhere, and anyone with an internet connection experiences it in effectively the same way. It’s non-consensually available in effectively every app — every Facebook, Google and Microsoft account, for example — and every media outlet known to man has mentioned AI multiple times since 2023. OpenAI and Anthropic might claim they need more data centers, but it’s unclear what “more data centers” actually achieves other than propping up NVIDIA and giving hyperscalers something to invest in.
A lack of data center capacity isn’t holding back people from using generative AI, nor is it stopping anybody from launching a product, nor can anyone actually express what it is that they’re being built for other than “reasons for Anthropic and OpenAI to spend money.” Anthropic’s supposed lack of compute did not stop it training or launching Mythos or Fable, and when it bought hundreds of megawatts of compute from SpaceX, the biggest news was that it expanded rate limits to allow users to burn $8,000 worth of tokens for $200 a month. Nothing about the painfully slow pace of data center development appears to be restraining a single AI company, the entire argument for more data centers appears to be “we need more compute so that people can buy it” far more than any cogent position around what these capacity shortages actually mean.
How much infrastructure do we need to spend $435 billion or more to justify the $1 trillion in GPU sales that NVIDIA claims it’ll have by the end of 2027? That’s how much demand we’ll need. As NVIDIA intends to sell over a trillion dollars of Blackwell and Vera Rubin GPUs by the end of 2027, it needs to have around (assuming a PUE of 1.35) 40GW of data center capacity built to support the 30GW+ of GPUs it will have sold. At about $12 a megawatt of critical IT (IE: the stuff in the data center that runs AI compute, and not everything else, like the cooling systems and any transmission loss), that’s $435 billion in purely IT capital expenditure before power, land, construction, labor, transmission, cooling, or any other costs.
OpenAI estimates it’ll spend $50 billion on compute in 2026, and Anthropic will likely spend comparable amounts. Outside of Microsoft, Google, Amazon renting or backstopping capacity for Anthropic and OpenAI — the only other tech firm with any meaningful compute spend is Meta (with Nebius and CoreWeave)... and Bloomberg is reporting that Meta is planning to start selling its compute because it doesn’t need all of it, yet another sign that actual, real demand does not exist at scale.
AI boosters with black mold problems will say “this is just to help them raise debt,” but that doesn’t hold up, considering the demand doesn’t appear to be there at scale with two-thirds of all venture capital funding focused on AI, and hyperscalers are sitting on massive remaining performance obligations — hundreds of billions of dollars’ worth — rather than the grim truth that 50% of hyperscaler RPOs are from Anthropic and OpenAI, hiding the fact that Microsoft’s RPO growth is flat year-over-year and Amazon’s is only growing at a modest 20% when you remove Anthropic and OpenAI’s hundreds of billions of dollars’ of compute spend. Google’s is a little messier, but the pattern holds. When everyone stops asking about your AI strategy or rambling on about “sovereign AI,” it’ll become blatantly obvious that the actual demand for AI was not particularly strong.
We have little compelling evidence that providing any inference-based services is profitable, which means that even if open source AI outlives the frontier AI labs, the unit economics are fundamentally broken. AI demand is, at this point, a direct result of societal pressure and non-consensually overwhelming customers with AI features. While there are people that like and pay for ChatGPT or Claude, vast majority of AI compute demand is from services provided to people either for free or sold at such a massive discount that it’s impossible that anyone on a $20 or $200-a-month plan could even afford these services had they paid their actual token cost. To paraphrase Cory Doctorow, your demand is based on selling $40 worth of compute for a dollar. That’s not a real business, nor is that organic demand.
AI evangelists claim scaling will drive costs down, but that would require them to… become cheaper. More compute isn’t (and hasn’t) lowering the cost of AI. Newer GPUs aren’t lowering the cost. Barely-tested Broadcom GPUs, Amazon Trainium XPUs, and Google TPUs aren’t lowering the costs. Even if they were to somehow magically do so in the future, what do we do with the mountain of H100, H200, B100, B200, B300 or AMD GPUs already deployed across tens of thousands of data center racks?
Every time I read somebody on Twitter say that “we’re early” or that “most people haven’t even tried agents” I feel like screaming. Motherfucker, everyone is talking about agents in every single media property all the time. AI boosters will refer to literally any AI feature as an agent, even if it’s a basic web search or generating code. The reason that most people are kind of “meh” about AI is that it doesn’t do things that they associate with AI (autonomously and automatically taking care of the things they need with little prompting or coaxing), everybody knows it hallucinates, and AI data centers are horrifying monoliths of capital that get massive tax breaks, use a ton of water, and are fronted by ultra-wealthy tech elites like Kevin O’Leary, or charmlessly disconnected Valley elitists like Altman and Amodei.
Every single person freaking out about “what if China does AI better than America” is living in a child’s fantasy. Oh no! Anthropic itself already admitted that cheaper open-source models — including Claude Haiku 4.5 and Kimi K2.7 — were able to identify the very same safety vulnerabilities as their flagship Fable model. National competition rhetoric is just a tool to justify public subsidies, tax handouts, and land giveaways to data center and land speculators. AI data centers are massive, expensive operations, and raising money to finish (or furnish) one after the bubble bursts will be very, very difficult.
I realize that everybody wants there to be a happy ending after all of this collapses. I get that it’s easier to think of things in familiar terms — even if said terms involved a 77% drop in the NASDAQ — because there was something good and nice at the end. People point to Uber or AWS as proof AI will eventually turn profitable, but those analogies do not hold. The market captured tech and business journalists and sell-side analysts that insisted on ignoring every warning sign and waving away problems by saying it was “just like Uber (nope!)” or “just like Amazon Web Services.” Between 2003 and 2015, Amazon spent $29.7 billion on capex for AWS, a fraction of the trillions being thrown at generative AI today, and AWS had tangible, enterprise-wide demand for cloud hosting long before LLMs existed.
AI Is Not Too Big To Fail — And You Can’t Bail It Out Anyway
Capital-hog Sam Altman has floated the idea of handing 5% of OpenAI to the US government, a stake worth around $42 billion. Altman and other OpenAI executives have suggested that each of America’s leading AI developers allot 5 per cent of their equity to a vehicle like the Alaska Permanent Fund, and considering OpenAI has projected to burn $852 billion through the end of 2030, that 5% stake would only exist to prolong the inevitable collapse.
This bubble is built on four interlocking unsustainable crises:
A data center speculation bubble, where we’re building AI GPU capacity in expectation of $450 billion or more in annual data center revenue for an industry that, without two unsustainable venture-backed labs, has only a few billion dollars’ worth of organic demand.
An AI startup bubble, where the vast majority of AI startups are both over-valued and have no foreseeable path to acquisition or a public offering. These startups also rely entirely on buying tokens from OpenAI and Anthropic, making them far more cash-intensive, soaking up the majority of global venture capital funding.
A private credit bubble, where asset managers have sunk billions of dollars of pension and insurance fund capital into unprofitable AI data center construction projects.
A semiconductor bubble, where supply chains have become saturated with artificial demand from those building AI data centers, inflating the cost of RAM and storage, making all consumer and enterprise electronics more expensive, including the hardware inside AI data centers themselves — creating a vicious cycle that has doubled the cost of a gigawatt data center from $50 billion to $100 billion in a little under 10 months.
To contextualize why AI cannot be treated like the 2008 financial crisis, let’s revisit the systemic risk of the banking collapse. If AIG had failed in 2008, it would have wiped out hundreds of billions in consumer savings, retirement accounts, municipal funds, and insurance policies across the globe. Small investors, including anyone who owned money market funds with A.I.G. securities could have been wiped out entirely. A little-discussed part of the scale of the 2008 bailout were the emergency liquidity mechanisms created to stop the bleeding — the Primary Dealer Credit Facilities (PDCF) and Term Securities Lending Facilities (TSLF) that provided as much as $100 billion dollars to banks and financial institutions every single trading day to prevent total market seizure.
By comparison, OpenAI and Anthropic are systemically irrelevant, much like the rest of the generative AI industry. While their existence props up the symbolic valuation of the US stock market’s Magnificent Seven, their actual economic footprint is tiny, outside of what I estimate is around $75 billion to $100 billion of 2026 compute spend and roughly $60 billion of combined top-line revenue. Remove those two firms, and the rest of the global AI industry’s annual revenue barely registers.
It’s also unclear what exactly you would bail out, unless the government’s plan is to feed them endless capital for all eternity until they somehow invent a functional profitable business model (so, forever). Neither of them carry massive balance sheet debt — and Broadcom is backstopping $30 billion of Anthropic’s $35 billion TPU hardware deal with Apollo Global Management — and their equity positions only matter to venture capital firms in the sense that their entire fund vintages will painfully underperform if OpenAI and Anthropic cannot IPO.
We Should Talk About SoftBank
There is exactly one large corporation that is systemically dependent on OpenAI: SoftBank. As I covered in this week’s Hater’s Guide to Softbank, SoftBank has wagered effectively its entire corporate future on $40 billion or more in short-term bridge loans to fund Sam Altman’s endless compute spending spree. If OpenAI cannot complete a public listing at its inflated private valuation, SoftBank will face an existential liquidity crisis.
This risk, again, is nothing compared to the global systemic collapse that would have unfolded if AIG or Lehman Brothers collapsed without intervention. That being said, SoftBank is one of the largest listed companies on the Japanese stock market, and its single largest investor is Japan’s $1.6 trillion government pension investment fund (GPIF), and thus SoftBank might secure some form of targeted Japanese state support down the line. That is an isolated regional corporate risk, not a global economic collapse risk tied to generative AI itself.
There is no avoiding the carnage to come, outside of a miraculous ten-to-one hundredfold explosion in organic commercial demand for AI compute by 2030 — a scenario that would require AI compute spending to outpace the entire $779 billion annual global software industry’s total revenue.
No bailout policy can reverse the downward trend once hyperscalers slash their capital expenditure budgets and NVIDIA’s GPU demand evaporates, which will in turn collapse the revenues of Taiwanese ODMs that build AI servers for hyperscalers, which will in turn crush the revenues of memory and storage semiconductor firms, triggering a prolonged industry-wide depression across the entire tech hardware supply chain — all created by Business Idiots that have no idea what to do other than hire people, fire people and burn billions of capital on unproven tools.
As I’ve said many times, investors and policymakers are conflating massive debt-fueled capital expenditures — driven by data center speculation and hyperscalers desperate for a new growth narrative — with real, diverse, sustainable commercial AI demand. Valuations are pumped up entirely on market sentiment rather than tangible unit economics, which means that when market sentiment takes a violent, permanent downward shift, there is no underlying fundamental revenue stream to prop up stock prices.
A sidenote on private credit: I am deeply worried about the private credit industry and its trillions of dollars of illiquid floating-rate loans, as we don’t really have full visibility on its total exposure to the AI bubble, other than that hundreds of billions of pension capital have been sunk into unfinished, unprofitable data center construction projects. Public pension funds are legally restricted from making massive direct punts on unprofitable AI infrastructure companies, but thanks to a massive regulatory loophole, they can make the same speculative bets by proxy by shuffling cash to opaque private credit funds.
The collapse in valuation of thousands of AI startups would not be meaningfully softened by a federal bailout unless the US government literally committed hundreds of billions of taxpayer dollars to buying worthless startup equity purely to prop up venture capital firms’ internal fund returns. Any such massive federal rescue package would have to pass both the House and the Senate, and any bailout of the AI sector would be an incredibly-unpopular political decision, infuriating progressive voters tired of Big Tech’s endless subsidies and conservative voters who claim to care about fiscal responsibility and working-class taxpayers.
As a reminder, the initial 2008 bank bailout bill failed its first congressional vote, with Republicans and Democrats each fairly split on support — and that rejection happened during a moment when the entire US financial system was actively imploding in real time. There is zero comparable emergency systemic risk from generative AI to force rushed bipartisan legislative action.
As far as the standalone data center bubble goes, the government is absolutely willing to let unfinished or abandoned industrial assets lay dormant for years on end. In the final quarter of 2008, 11% of all US residential homes sat empty, or 15% if you include vacation properties. Unlike AI data center hardware, physical land retains residual value even if you haven’t built a giant warehouse full of loss-making GPUs on top of it. There isn’t a policy or economic imperative for a federal bailout here, and one will never be forthcoming. After the Global Financial Crisis, thousands of construction firms were allowed to collapse entirely, to the extent that the total number of construction companies operating in America halved between 2007 and 2012.
You could argue that future presidential administrations will hand out sweetheart tech subsidies or targeted rescue packages, but that speculative talking point is not serious financial analysis. If every rebuttal to structural AI bubble risk reduces to vague fearmongering about presidential corruption, you are catastrophizing rather than analyzing market fundamentals.
And, most crucially, the vast majority of big tech will be fine, at least in the short term, when the bubble bursts. NVIDIA will likely cease being the largest company on the stock market, and the Magnificent Seven will suffer a dramatic drawdown in market cap, but outside of unforeseen horrendous financial decisions, the worst outcome I could see would be multi-billion-dollar asset write-downs for Microsoft, Google, Meta, and Amazon, and potential SEC regulatory action against NVIDIA if it is proven to have illegally routed advanced GPUs to China in violation of export controls.
This does not mean that retail investors, tech workers, semiconductor supply chain employees, pension holders, and everyday citizens won’t suffer massive financial harm as they always do when asset bubbles burst. Tens of thousands of AI industry layoffs, trillions in erased paper wealth, inflated hardware costs for all consumer electronics, and cascading losses across private credit funds will create widespread economic pain for ordinary people with no connection to Silicon Valley’s elite bubble culture.
Which is why I am making a firm, clear statement to end this piece.
When The Time Comes, Let The AI Industry Burn
I repeat myself:No bailouts, no handouts, no special treatment, no tax breaks, no CHIPS act carve-outs, and no sovereign wealth fund dedicated to propping up generative AI. It is time to tell the AI industry to go fuck itself, because it’s effectively done the exact same to the rest of society. These companies must be forced to stand on their own two feet and collapse with dignity if their wretched, unprofitable business models cannot sustain themselves without endless external capital infusions.
The world’s governments have rolled over and shown their bellies to the tech industry for far too long, and have been aggressively conned by some of the richest people alive into believing that Sam Altman and Dario Amodei are building anything other than the world’s least-profitable mass-market software product line.
We do not need a “sovereign AI strategy,” nor do we need “a sovereign AI wealth fund,” nor do we need to “make sure America leads in AI,” at least not when we’re talking about large language models — the underlying technology of ChatGPT and Claude, two of the most over-hyped and deceptively-marketed pieces of software in human history.
Whether or not LLMs are a minor niche productivity tool is irrelevant, because the AI industry has demanded the world hand it unlimited land, unlimited money, and unlimited scarce natural resources to continue proliferating a technology that has only ever lost money and has no long-term path to sustainable profitability. The only reason it has gained any mainstream traction at all is because the entire tech industry unified around it as a desperate distraction to hide from the hard truth that it has no next paradigm-shifting consumer or enterprise product to drive growth, and nothing an LLM can remotely do justifies the trillions in capital poured into it.
And it has only gotten this far because of a captured business and tech media ecosystem that systematically overstates its capabilities and hand-waves away its obvious accuracy flaws and existential economic instability. There are far too many journalists, analysts, and commentators easily wooed by charismatic wealthy founders who promise they’re building sentient machine intelligence, and when the markets bleed red by the trillions, these people must accept their share of responsibility for stoking mass speculative mania. So much of the so-called AI journalism published since late 2022 has been weaponized to further enrich the already ultra-wealthy and inflate a catastrophic asset bubble that will inflict lasting financial harm on hundreds of millions of regular people globally — all while Sam Altman and Dario Amodei remain billionaires even if their core companies collapse entirely.
When the time comes, the AI industry must burn. It must be allowed to fail wholesale. Generative AI has already been given far too much money, media oxygen, political deference, and scarce planetary resources, and if it cannot survive without continual venture capital infusions and unceasing media coddling, it is entirely unworthy of societal protection and must face the cold, hard market reality that every regular person faces when their business or career collapses.
There is no magic “bailing out” these broken firms. Handing $42 billion in public capital to OpenAI or Anthropic will not fix their structurally broken unit economics, nor will it conjure up the $400 billion or more in annual organic commercial revenue required to substantiate just NVIDIA’s projected AI GPU sales through the end of 2027.
These people are not building a transformative shared future — they’re inventing new mechanisms to re-entrench existing wealth concentration, to give Microsoft, Google, Amazon and Meta new excuses to inflate their recurring revenue streams and centralize global computing infrastructure under the marketing auspices of “innovation.”
If any policy makers read this, know that you’ve been systematically conned by the AI industry lobby. They want you to believe they’re economically essential solely so you’ll bail them and their wealthy venture capital backers out when the bubble pops, or funnel unlimited taxpayer funds into building them tax-subsidized data center campuses across your districts. They are not building autonomous general artificial intelligence, nor will they ever deliver on that decades-old promise with current LLM architectures.
I think it’s naive to imagine there would ever be meaningful personal legal consequences for the architects of this bubble, but if systemic regulatory and policy reforms emerge after the crash, the people to hold fully accountable are Sam Altman, Dario Amodei, Satya Nadella, Sundar Pichai, Andy Jassy, Jensen Huang, Mark Zuckerberg, and every other C-suite executive who forcefully manufactured mass public consent for a technological dead end and laid the financial groundwork to serve the world its next great global financial crisis.
Until fundamental structural reform hits the tech sector, Silicon Valley will never be capable of building anything other than consensus-driven hype cycles and tools that reinforce the existing wealth status quo.
So, spit in the face of any politician, lobbyist or executive who even hints at a targeted AI bailout, refuse to entertain their demands for new tax breaks and state subsidies, and demand that they do the complex, ugly, unglamorous work of weighing the actual long-term economic consequences if the entire industry’s collective assumptions about generative AI turn out to be completely wrong. When this AI era ends, we will need to thoroughly excavate every layer of the collapse to make sure this exact speculative mania never happens again, identifying every media outlet, venture fund, corporate executive and personality that was used to manufacture mass consent and spread unsubstantiated mythology about LLMs as world-changing technology.
Every major asset bubble that has ever occurred has mostly left the architects of risk unexamined and unpunished after the dust settles. The economic carnage I fear will follow this era’s collapse will be widespread and brutal for ordinary households, and we must do everything in our power to both thoroughly understand exactly how we arrived at this moment and implement permanent guardrails to ensure it cannot repeat itself — which will involve many painful national conversations about our unregulated private financial system, captured mainstream media ecosystem, and how speculative technological innovation is funded, valued, acquired and subsidized.
The same reckoning applies to the online cult acolytes of this AI era. There are millions of people online who have developed a genuine hostile resentment toward anyone who does not immediately accept a for-profit tech corporation’s marketing messaging as objective scientific truth. This cult-like fanaticism within the broader tech audience is a deep cultural sickness that must be dismantled once and for all.
Much of this coming market reset will be unavoidable, because I think what directly follows the AI bubble will be a massive industry-wide revaluation of the entire tech sector, a necessary reality check for a Silicon Valley culture that’s far more beholden to Wall Street capital than it is to human progress or broad societal benefit. The cults of personality that dominate this industry do not care about you, or me, or any working person other than the billionaires they worship and their imagined place in a stratified society dominated by the ultra-rich and their unelected cronies.
I refuse to accept their narrow, self-serving vision of the future as an inevitable fate for humanity.
As I said a few weeks ago:The AI bubble is sold to the public as humanity’s inevitable technological future, but it actually resembles the drawn-out, expensive death of mid-era Silicon Valley. Only a tech industry entirely dominated by symbolic paper wealth and hollow value creation would ever tolerate a trillion dollars of total waste chasing a still-theoretical, unproven long-term outcome, and only an intellectually hollow, capital-addicted Valley culture would be so easily grifted by charismatic hucksters like Dario Amodei and Sam Altman.
This era must end, and all failed AI firms must be fully allowed to fail without public rescue.
Let AI burn.
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Ed ZitronView all articles
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