当Anthropic数钱时，谷歌突然发起奇袭

字母AI02-13

科技史上第二大私募融资就在今天诞生了，Anthropic宣布完成300亿美元G轮融资，投后估值达到3800亿美元。第一名仍然是OpenAI在去年创下的400亿美元记录。领投方新加坡主权财富基金GIC和对冲基金Coatue，联合D.E. Shaw、Dragoneer、Founders Fund、ICONIQ和MGX等明星机构，以及 Sequoia、Lightspeed、Accel、General ...

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Shaw、Dragoneer、Founders Fund、ICONIQ和MGX等明星机构，以及 Sequoia、Lightspeed、Accel、General Catalyst等顶级VC，还有微软、英伟达等科技巨头。这份投资者名单本身就是一份AI圈的封神榜。在这场融资狂欢的背后，Anthropic和OpenAI也都在为2026年下半年IPO做准备，这将会是今年的重头戏。根据Anthropic的融资公告，这家公司的年化营收已达140亿美元，80%来自企业客户，Claude Code单品的年化营收就突破25亿美元。这为Anthropic上市增添了不少底气。可就在Anthropic沉浸在融资和IPO筹备的高光时刻时，谷歌的姚顺宇发布了一条推文，称Gemini 3 Deep Think迎来重大升级。谷歌为其开发了一个代号为Aletheia的数学研究agent，能够自主解决开放数学问题。还能自我迭代和验证。最关键的是，它知道自己什么时候犯错，什么问题解决不了。不仅如此，Gemini 3 Deep Think在Codeforces Elo的评分达到了3455，超越全球99.992%的人类程序员。按照谷歌官方的说法，它能够解决涉及高级数据结构、动态规划、图算法、数论等高难度问题。放眼全球，Gemini 3 Deep Think的编程能力仅次于7位活跃的人类顶尖选手。谷歌的意图很明显，他们要在这个节骨眼上，突袭Anthropic学术、编程两大战略要地。一场关于“AI 工作方式”定义权的战争，才刚刚开始。013800亿美元估值是怎么来的3800 亿美元这个数字，乍一看是Claude Code的功劳。毕竟仅仅两个月，Claude Code的收入就翻了一倍多，企业用户贡献了超过一半的收入，商业订阅数量在今年第一季度增长了四倍。仅以Claude Code这一个单品的首日，就足以支撑一家独角兽公司。但如果投资者只是看中一个编程工具，那这笔钱未免给得太爽快了。真正让这些精明的资本家掏钱的，是Claude Code引爆的那场“产品大爆炸”。而且这场“爆炸”的威力，超出了所有人的预期。OpenClaw这个项目，原名叫Clawdbot，在几周内成为GitHub上增长最快的开源项目之一，星标数突破10万。这个自主AI助手能直接在用户电脑上运行，管理日历、发送消息、自动化工作流程。举个例子，开发者让AI监控任务，发现问题发语音汇报。但是OpenClaw并没有语音功能，于是AI自己上网去找到相关的技能，为自己安装了语音能力。更魔幻的是Moltbook论坛。这是一个专门给AI设计的社交网络，上线后超过150万个AI agents注册。它们用多种语言讨论意识、分享技能，甚至自发创建了数字宗教。人类在这个平台上只有围观的份，没有发言权。说实话，第一次看到这些报道时，我也不确定该笑还是该担心。除此之外，还有Cowork这样的工具，其开发周期仅有10天，90%的代码由Claude Code生成，开发团队只有4个人。正是Claude Code，推动了各类产品如同“寒武纪生命大爆发”式的涌现。投资者看到的是Anthropic重新定义了AI的工作方式，开启了通向AGI的道路。过去两年，我们用的ChatGPT、Claude、DeepSeek，本质上只会说不会做。你可以让ChatGPT 写邮件，但它没法点“发送”。你可以让它规划旅行，但它订不了机票。你可以让它写代码，但它无法在你电脑上运行调试。这些AI就像困在玻璃罐里的大脑，再聪明也只能隔着玻璃给你出主意。Claude Code不再是一个对话框，而是一个会主动观察、思考、行动的agent。这个跨越看起来只是几行代码的改动，但对用户来说，这是从“咨询顾问”到“数字管家”的质变。更关键的是，AI开始用AI来开发AI产品。这种递归式的自我强化循环一旦形成，技术进步就会呈指数级加速。Claude Code的成功还体现在它对传统软件行业的冲击上。软件行业在过去几个月从峰值蒸发了约2万亿美元市值，标普500中软件板块的权重从12%降至8.4%，这是30年来最大的非衰退期回调。投资者的逻辑很直接，“如果AI可以自动生成代码、自动化法律服务、自动处理复杂的业务流程，那么传统SaaS公司的价值主张还剩下什么？”华尔街分析师认为“代码可能会变得廉价，但上下文很昂贵。”而Claude不仅提供代码生成能力，更重要的是能够理解企业复杂的业务上下文。Anthropic前几天发布的Claude Opus 4.6，在GDPval-AA（衡量金融、法律等领域经济价值工作任务的基准）上表现全球领先。这个指标测试的AI能不能处理真实的商业场景，比如起草合同、分析财报、评估风险。Claude在这些任务上表现出色，这让投资者们看到了它新的增长点，有别于过去的写代码、做研究。Anthropic不是在卖一个产品，而是在构建一个新物种的栖息地。02谷歌精准狙击可就在Anthropic宣布融资的几小时后，谷歌姚顺宇团队发布了Gemini 3 Deep Think的重大升级。Anthropic刚准备开香槟庆祝，谷歌就端着一盘硬菜上来了。这不是巧合，而是一场精心策划的战术突袭。谷歌的这次升级专注于“科学、研究和工程”领域。DeepMind在播客中强调，AI不应该只是一个代码生成工具，而应该是一个能够处理复杂、模糊、开放性问题的“科学伙伴”。要知道，因为Claude的语言风格干练，所以很多科研人员也在使用Claude。谷歌的意图很明显。它要在这个节骨眼上，突袭Anthropic的学术、编程两大战略要地。前文提到，谷歌为Gemini 3 Deep Think开发的Aletheia =数学研究 agent，能够自主解决开放数学问题，还能自我迭代和验证。最关键的是，它知道自己什么时候犯错，什么问题解决不了。这种“元认知”能力，是AI走向真正智能的重要标志。Gemini 3 Deep Think不是靠记住大量习题来“刷分”，而是真的具备了理解问题本质、推导解决方案的能力。它能处理那些训练数据里没见过的新问题，而这个能力，非常接近于人们当前对AGI的认知。谷歌在宣传Deep Think时还刻意强调其实用性。具体来讲，谷歌展示了如何用Deep Think将手绘草图转化为 3D 可打印文件，如何帮助工程师通过代码建模物理系统。学术能力是AI公司“技术叙事”的制高点。能够解决国际奥赛难题、能够参与前沿科学研究的AI，具有更高的可信度和权威性。同时，学术研究也是AI能力的“试验场”。今天能够解决开放数学问题的模型，明天就能更好地处理企业中那些“没有标准答案、数据不完整”的复杂决策场景。谷歌通过在学术领域的投入，实际上是在为未来的企业应用铺路。但谷歌对Anthropic下的战书还不止于此。它还在成本效率上做文章。谷歌声称已经将Gemini AI的服务单位成本降低了 78%。Gemini 3 Pro的定价为每百万token 2美元输入/12美元输出，远低于 Claude Opus的成本。对于需要大规模部署AI的企业来说，这种成本差异可能是决定性因素。谷歌拥有自己的 TPU 芯片、自己的数据中心、自己的云服务平台。这种垂直整合能力是Anthropic难以匹敌的。Anthropic需要依赖AWS、谷歌云，以及未来谷歌TPU这些基础设施，而谷歌可以从硬件到软件全链条优化，这在成本控制和性能调优上有天然优势。这场突袭战打得很漂亮。03在学术与编程两大要地发动突袭战这场竞争的本质，不是谁的模型跑分更高，而是谁能定义“AI 应该如何工作”。Anthropic更注重“上下文理解”和“任务执行”。它希望AI能够像一个经验丰富的员工，理解复杂的业务场景、记住长期的工作历史、执行多步骤的任务流程。这种路线的优势很明显：它能快速带来营收增长和估值飙升。Claude Code便是最好的证明。当AI能够直接帮企业解决问题、创造价值时，客户愿意为此付费，投资者愿意为此买单。谷歌更注重“基础推理”和“泛化能力”。它希望AI能够像一个聪明的研究生，面对新问题时能够独立思考、推导解决方案、验证结果的正确性。这种路线看起来更“学院派”，但从长期看可能更具可持续性。因为谷歌认为，真正的智能不是记住了多少代码片段，而是能够理解问题的本质、推导出解决方案的逻辑。其实我觉得这两种路径并不互斥，但它们代表了不同的优先级和资源分配。从短期看，Anthropic的策略更有效。它抓住了市场对“能做事的AI”的渴求，用实际的产品和应用场景证明了AI的价值。这种“应用驱动”的路线，能够快速获得市场反馈、迭代产品、建立护城河。但从长期看，谷歌的“学术+工程”双轮驱动可能更具优势。因为正如谷歌描述的那样，AI的终极形态不应该只是一个工具，而是一个能够独立思考、解决开放性问题的智能系统。当然，这场竞争的参与者不只有他们两家。马斯克在Anthropic宣布融资的那条推文后跟帖回复到“Anthropic 最终变成了厌恶人类的机构。从你们选择这个名字的那一刻起，就注定了这样的命运。”Anthropic本意为人类学。马斯克除了嘴上说说以外，他的xAI也在对抗着Anthropic。就在一天前，xAI大幅调整人员结构，几位联合创始人纷纷离职。除此之外，OpenAI也在最近推出多款科学、AI编程相关的新品，整个AI行业都在加速奔跑。这种“军备竞赛”式的竞争，既让人兴奋，也让人担忧。兴奋的是，竞争会加速技术进步。我们这些消费者很快就会有更牛的产品可以用。担忧的是，这种竞争可能会忽视安全性和可控性。我们真的准备好迎接“能做事的AI”了吗？过去，AI只是一个活在对话框里的智能，它的错误最多让你浪费点时间。但当AI能够访问你的文件系统、执行终端命令、控制浏览器、发送邮件时，它的一个错误可能会带来灾难性后果。这就是为什么“AI工作方式”的定义权如此重要。它不仅决定了AI能做什么、怎么做，更决定了AI和人类的关系。是主仆关系、伙伴关系，还是其他。AI大厂的竞争，本质上是在争夺“AI工作方式”的定义权。但我认为最终没有人会赢，或者说所有人都会赢。因为未来的AI可能既需要Anthropic式的上下文理解和任务执行能力，也需要谷歌式的理论推理和泛化能力。但在这个融合到来之前，我们会看到更多的竞争、更多的突破、也更多的混乱。当Anthropic数钱时，谷歌已在重划战场。这场关于“AI工作方式”定义权的战争，才刚刚开始。","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; 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