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"title": "Google连失两AI大将!AlphaFold之父奔向Anthropic、Transformer共同作者投靠OpenAI",
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"description": "Google AI 版图遭遇重大挑战。AlphaFold 之父、诺贝尔化学奖得主 John Jumper 宣布离开 DeepMind 加入 Anthropic;Transformer 共同作者 Noam Shazeer 则转投 OpenAI。",
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"content": "<p>Google(<a data-symbol-template=\"USS:GOOGL:STOCK:COMMON\" href=\"#\">GOOGL-US</a>) 的人工智慧(AI)人才版图,在近日出现剧烈震荡。先是 Transformer 架构共同作者 Noam Shazeer 宣布离开 Google、投奔 OpenAI;紧接着,AlphaFold 之父、诺贝尔化学奖得主 John Jumper 也在 X 上亲自宣布,将在任职近九年后离开 Google DeepMind,转而加入其直接竞争对手 Anthropic。</p>\n<p style=\"text-align:center;\"><img src=\"https://cimg.cnyes.cool/prod/news/6506049/l/cf03eacc4225ea8346e338d32c3f1896.jpg\" alt=\"Google连失两AI大将!AlphaFold之父奔向Anthropic、Transformer共同作者投靠OpenAI\" style=\"width:50%;height:auto;border-radius:6px;margin:15px auto;display:block;\"></p>\n\n\n<p>两天之内,Google 眼睁睁看着两位足以改写 AI 产业史的人物,分别被 OpenAI 与 Anthropic 收入麾下。</p>\n\n<h6><strong>AlphaFold</strong><strong> 之父跳槽</strong><strong> Anthropic</strong></h6>\n\n<p>Jumper 是 AlphaFold 蛋白质结构预测系统的核心人物。</p>\n\n<p>消息一出,DeepMind 执行长 Demis Hassabis 几乎立即在 X 上回应,感谢 Jumper 过去九年的「非凡合作」,并强调 AlphaFold「改变了世界」。</p>\n\n<p>九年前,正是 Hassabis 亲自拍板,让博士毕业仅六个月、毫无管理经验的 Jumper 领导 AlphaFold 团队;如今,这份知遇之恩似乎也未能留住人才。</p>\n\n<p>Jumper 1985 年生于美国阿肯色州,2007 年取得范德堡大学物理与数学学士后赴剑桥大学攻读理论凝聚态物理,发现方向不合仅取得硕士便离开。</p>\n\n<p>随后他在纽约 D.E. Shaw Research 从事蛋白质与过冷液体的分子动力学模拟三年,2011 年重返芝加哥大学攻读理论化学博士,将机器学习应用于蛋白质折叠研究。2017 年取得博士学位后,同年底加入 Google DeepMind。</p>\n\n<p>2020 年,AlphaFold 2 问世,将蛋白质 3D 结构预测准确率提升至平均九成,攻克困扰生物学界半世纪的难题,如今已在 190 个国家、超过 200 万名研究人员使用,预测结构数量超过 2 亿个,广泛应用于疟疾疫苗、癌症治疗与抗药性细菌研究。</p>\n\n<p>随后的 AlphaFold 3 更将预测能力扩展至 DNA、RNA 与小分子。2024 年,他与 Hassabis 共同站上诺贝尔化学奖颁奖台,成为第 100 位与芝加哥大学有关联的诺奖得主。离职时职衔为 DeepMind 副总裁、工程院士。</p>\n\n<p>外界对其离职原因的解读,聚焦在「推力」与「拉力」两端。据《彭博》报导,Jumper 近期工作其实与 Google「AI 程式开发团队」高度相关,而 DeepMind 内部近月有员工与高阶主管担忧,公司在面向企业的 AI 程式开发工具上缺乏清晰策略,这正是 Anthropic 与 OpenAI 领先的领域。</p>\n\n<p>另一方面,Anthropic 今年在生命科学领域投入可观资源:去年 10 月推出 Claude for Life Sciences,今年 4 月以约 4 亿美元全股票收购计算生物学团队 Coefficient Bio,6 月 30 日还将举办「The Briefing: AI for Science」线上活动。</p>\n\n<p>一位诺奖级蛋白质结构专家此时加入,路线高度吻合。</p>\n\n<h6><strong>Transformer</strong><strong> 共同作者:</strong><strong>从</strong><em>柏克莱</em><strong>辍学生到「最贵在逃牛人」</strong></h6>\n\n<p>如果 Jumper 的故事是科学界的传奇,Shazeer 的经历则更像一部 AI 创业剧本。</p>\n\n<p>1994 年,Shazeer 拿下国际数学奥林匹克竞赛金牌;2000 年从柏克莱辍学进入 Google,成为公司前 100 名员工之一。</p>\n\n<p>他早期改良了拼字检查器,后来撰写了 AdSense 核心演算法 PHIL,协助 Google 打磨出极具效益的广告系统。此后 21 年间,他从工程师一路升至副总裁,见证了整个网路时代的演进。</p>\n\n<p>他在 Google 最关键的贡献,是 2017 年那篇仅 13 页、由 8 位作者共同完成的论文《Attention Is All You Need》,并排名第二作者。</p>\n\n<p>这篇论文提出的 Transformer 架构,奠定了如今所有大型语言模型的基础,从对话、搜寻到程式码补全,几乎所有 AI 产品背后都运行着这套架构。</p>\n\n<p>论文发表后,Shazeer 希望进一步将 Transformer 打造成真正能与人对话的产品,他与团队开发出聊天机器人 Meena,后改名为 LaMDA。尽管内部评估效果良好,Google 基于安全与品牌考量,迟迟未对外发布。</p>\n\n<p>等待多时后,2021 年 Shazeer 决定离开,带着 LaMDA 首席设计师 Daniel De Freitas 共同创办 Character.AI,让使用者能与各种个性化 AI 角色对话,迅速成为消费端 AI 产品的现象级案例,估值飙升至十几亿美元。</p>\n\n<h6><strong>27</strong><strong> 亿美元的回购交易</strong></h6>\n\n<p>分析称,要理解 Google 随后砸下 27 亿美元的举动,得回到 2022 年 11 月 OpenAI 推出 ChatGPT,用户数仅两个月便突破一亿,震撼整个科技产业。</p>\n\n<p>据报导,Google 内部当时的反应可用「恐慌」形容,不仅启动红色警报,半退休的共同创办人 Sergey Brin 也被重新召回参与会议。然而,当时公司内部最熟悉 Transformer 底层架构的人选,早已不在 Google 阵中。</p>\n\n<p>2024 年 8 月,Google 与 Character.AI 签署约 27 亿美元的技术授权协议。表面上是技术交易,业界普遍理解这笔钱主要是为了让 Shazeer 回归。</p>\n\n<p>他重返 Google 后,出任 Google DeepMind 副总裁,并担任 Gemini 专案共同负责人。</p>\n\n<p>在他带领下,Gemini 确实交出成绩单。到 Gemini 3 这一代,模型在大型语言模型评测平台 LMArena 上登上全球第一,深度推理能力大幅提升,博士级科学问答正确率超过九成,高中数学竞赛题目全数正确,程式撰写能力也跻身第一梯队,Google 内部称此为「Gemini 时代」的开启。</p>\n\n<p>分析指出,就数字成果而言,这笔 27 亿美元的投资,看起来没有白花。</p>\n\n<h6>为什么 Shazeer 还是走了?</h6>\n\n<p>一切看似顺利,直到 2026 年 6 月 18 日,Shazeer 在 X 上发文宣布:加入 OpenAI。</p>\n\n<p>对 Shazeer 而言,金钱显然不是离开的理由。他个人身价已逼近 10 亿美元。真正的问题,在于 Google 这类大型企业的组织结构本身。</p>\n\n<p>Google 旗下 AI 相关人才规模上万人,光 DeepMind 内部就将近一万人,且分散在 Gemini、开源模型 Gemma、影片生成 Veo、TPU 晶片研发、DeepMind 基础研究,以及 Google Brain 遗留专案等多条不同产品线,各自拥有独立的绩效指标、汇报体系与优先顺序。</p>\n\n<p>分析称,这正是大型企业常见的「部门深井」现象,表面上人才济济,实际上部门之间缺乏流通。</p>\n\n<p>在这种规模的组织里,推动一件事的成本往往不是技术难度,而是内部协调的系统性摩擦:光是厘清汇报对象、预算审批与跨部门整合,就可能耗费数日,等真正动手时,市场机会的窗口可能已经错过。</p>\n\n<p>相较之下,OpenAI 被外界视为一家「AI 原生」公司,正以最快速度透过 AI 重塑自身组织。该公司积极招募人才、加大投入、加速产品节奏。</p>\n\n<p>据报导,Meta 过去曾开出最高 1 亿美元的签约奖金抢人,OpenAI 随后将员工平均年股票补偿提升至超过 150 万美元。</p>\n\n<p>但业界观察认为,这已不仅是薪酬数字的竞赛。最顶尖的研究人才,往往不只看待遇,更看重组织的发展势头与动能,他们的选择本身就具有风向标意义。</p>\n\n<p>值得一提的是,先前 AI 研究者 Andrej Karpathy 也选择加入 Anthropic。目前尚不清楚还有多少顶尖研究人员正在悄悄物色下一份工作,但整体趋势已相当明显。</p>\n\n<h6><strong>Gemini</strong><strong> 模型是否也已落后</strong><strong>?</strong></h6>\n\n<p>接连失去两位关键人物的同时,也让外界重新质疑:DeepMind 在模型本身的竞争力上,是否同样面临压力?</p>\n\n<p>根据 Artificial Analysis 智慧指数,Anthropic 新推出的模型一上线即登顶榜单,且大幅领先第二名,前两名皆由 Anthropic 模型包办,相较之下 Google 的 Gemini 评分已退居第二梯队之外,甚至被中国开源模型智谱 GLM-5.2 反超。</p>\n\n<p>备受期待的 Gemini 3.5 Pro 则一再延期,该模型虽于 5 月 19 日 Google I/O 大会上预告,执行长 Sundar Pichai 当时承诺「再给我们一个月」却引来台下嘘声,但截至 6 月中旬,仍仅对部分 Vertex 企业客户提供有限预览,尚未正式对外公开。</p>\n\n<p>另有网路传言指出,DeepMind 内部团队弥漫着沮丧情绪,有员工直言:在文字、图像、影片、语音甚至视觉等领域都缺乏站上技术最尖端的模型,即便投入大量资源、耗费数月时间仍无法推出真正具突破性的产品,令人质疑公司方向是否出了问题。</p>\n\n<p>人才出走与模型竞争力的双重压力下,Google 接下来如何留住核心研究人才、加速产品节奏,将是观察其 AI 战略能否维持领先地位的关键指标。</p>\n<div class=\"related-articles seo-links\">\n <h4>相关阅读</h4>\n <ul>\n <li><a href=\"/new/mg/article-717.html\" title=\"比辉达快10倍!美光科技市值从5000亿到1兆美元 只用48天创美股史上最快纪录\">比辉达快10倍!美光科技市值从5000亿到1兆美元 只用48天创美股史上最快纪录</a></li>\n <li><a href=\"/new/mg/article-13241.html\" title=\"〈美股早盘〉主要指数涨跌互见 市场静待华许杰克森霍尔演说\">〈美股早盘〉主要指数涨跌互见 市场静待华许杰克森霍尔演说</a></li>\n <li><a href=\"/new/mg/article-11228.html\" title=\"美国上周初领失业金人数升至20.9万 劳动市场仍保持稳定\">美国上周初领失业金人数升至20.9万 劳动市场仍保持稳定</a></li>\n <li><a href=\"/new/mg/article-1785.html\" title=\"AI点燃财富效应 全球百万富翁一年激增近200万人、富人更富\">AI点燃财富效应 全球百万富翁一年激增近200万人、富人更富</a></li>\n <li><a href=\"/new/mg/article-3793.html\" title=\"AI需求续旺!美光开盘大涨近19% 市值一度超越Meta\">AI需求续旺!美光开盘大涨近19% 市值一度超越Meta</a></li>\n <li><a href=\"/new/mg/article-6084.html\" title=\"Meta自研AI晶片9月投产带旺晶片股 花旗、小摩同步看多「这些设备股」\">Meta自研AI晶片9月投产带旺晶片股 花旗、小摩同步看多「这些设备股」</a></li>\n </ul>\n</div>",
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