今天,我与谷歌及 Alphabet 首席执行官桑达尔·皮查伊进行了一场对话,录制时间是在谷歌 I/O 开发者大会之后。这是我连续第五年在 I/O 大会后与桑达尔坐下来交流,这已成为我最喜爱的《解码器》传统之一。
I/O 大会总是新闻不断,今年也不例外——谷歌推出了强大的新 Gemini 大语言模型,将 AI 智能体融入所有产品,并对网页搜索和 YouTube 搜索进行了重大变革,这些变化将再次重塑信息生态。
要聊的内容很多,桑达尔和我深入探讨了所有这些话题。但我也意识到,我已经很久没有向桑达尔提出《解码器》关于组织架构和决策制定的问题了,所以我从那里开始切入。你会听到桑达尔说,几年前在 ChatGPT 出现后,他意识到需要重新思考谷歌的运作方式,并为此进行了大量高管调整和重大决策,以使公司采取更具进攻性的姿态。
当然,我们也谈到了所有那些搜索变革,以及将新型智能搜索框与公司新的 Gemini Spark 智能体平台整合在一起,似乎显然是谷歌搜索的真正未来。这样一来,搜索可以触发任务,而不仅仅是提供结果。这令人兴奋,但似乎很可能再次改变开放网络的动态格局。
如果你是《解码器》的听众,你会知道我在几年前创造了“谷歌归零”这个说法——即随着谷歌直接在搜索结果页面上回答越来越多的查询,网站从谷歌获得的流量将降至零。这个概念从桑达尔在以往采访中回避的观点,变成了整个媒体行业都在应对的现实。就连康泰纳仕等大型出版商的 CEO 现在也公开表示,他们正在为未来零搜索流量的世界做规划。
谷歌还在用 YouTube 视频训练其模型,并改变 YouTube 搜索功能,对视频进行摘要和索引,以便用户能直接跳转到相关部分。这肯定会引起一些创作者的焦虑,所以我问桑达尔,他是否准备好像目前与出版商斗争那样,与 YouTube 创作者展开同样的较量。
最后,我问桑达尔,谷歌 DeepMind 首席执行官德米斯·哈萨比斯在 I/O 大会主题演讲结尾时表示,我们正处于“奇点时代的山脚下”。桑达尔同意德米斯的观点并不令人意外,但他对 AGI 时间线的看法值得关注。
就像我说的,这是我每年最喜欢做的节目之一,因为桑达尔总是乐于回答问题——甚至愿意和我一起在手机上查看搜索结果。我相信你会非常喜欢今年的这次对话。
好的:桑达尔·皮查伊,Alphabet 和谷歌的首席执行官。我们开始吧。
本次采访为篇幅和清晰度考虑,做了少量编辑。
桑达尔·皮查伊,你是 Alphabet 和谷歌的首席执行官。欢迎回到 Decoder。
很高兴来到这里。很高兴再次见到你,尼莱。
这是我每年最喜欢的对话之一。我想我们已经在 I/O 大会上做了差不多五次了。
哇。我都没意识到已经五次了,但我很享受。再次感谢。
我想先来一轮快问快答。我一直在想这件事。我们聊过很多。我们总是深入探讨网络、搜索以及宏大的思想,但我意识到我已经很久没有问过你 Decoder 的那些问题了。
我刚刚回顾了我们之前的对话,以及谷歌本身,你确实对谷歌做了很多改变。我想你的一些直接下属也换人了。你显然重组了 DeepMind、平台与设备以及 Android 部门。跟我说说谷歌现在的架构是怎样的。
好的。现在是谷歌和 Alphabet。显然我们还有 Alphabet,但广义上我认为谷歌有三大业务:搜索、YouTube 和谷歌云。我们运营着巨大的平台,包括 Android、Chrome 以及与之相关的整个领域。而支撑这一切的是所有这些重要的技术领域,即人工智能和我们的基础设施工作。此外还有与之配套的职能部门。
但从宏观层面来看,你可以将其理解为搜索、YouTube、谷歌云,以及我们的大型计算平台。这些是主要业务板块,当然,它们都由 Google DeepMind 和我们的基础设施团队提供技术支撑。这是理解其架构的一种简单方式。当然,除此之外我们还有其他布局,Waymo 是其中最突出的一个,但还有很多很多其他项目,比如 Isomorphic Labs 等等。
我想把重点放在谷歌本身。我觉得我们可以花整整一个小时来讨论 Alphabet 及其架构,以及它作为一家拥有众多业务的上市公司是如何运作的。但暂且只聚焦于谷歌,外界对谷歌历来有一种批评,认为这是一家推出大量产品的公司。产品太多就难以销售。缺乏足够的专注度。有成千上万种不同名称的产品,彼此之间以各种方式重叠。
在我看来,这种状况的根源在于,你确实进行了这些大规模的基础设施投入。你拥有了所有这些能力,而负责各个业务的人可以利用这些能力快速推出产品。但可能缺乏足够的统筹或集中规划,比如“我们是不是推出了两个相同的东西?”你如何解决这种矛盾?谷歌似乎确实变得稍微更专注了一些,但公司的文化就是:“我们要做很多尝试,看看哪些能成功。”你对此是如何处理的?
我们的行动也充满了意图。我认为,我们拥有 13 个各自拥有十亿用户的产品并非偶然,并且我们对这些产品有着长期的承诺。你可以回想一下 Gmail、地图、谷歌文档、搜索或 Chrome 浏览器推出的时候。我们在许多领域也长期保持着深入和持续的努力。
在 AI 时代,我将其内化的一种方式是:我们首次拥有了如此统一的底层基础设施,通过我们的 Gemini 模型和底层 AI 基础设施来驱动所有这些产品。因此,我们能够更有意图地去做一些跨产品的事情。个人智能就是一个很好的例子。这是一项统一的工程。用户可以在每个产品中选择开启它,但它构建在同一个底层基础设施之上,从而在我们的产品中提供一致的体验。
底层的 Gemini 模型本身就是一个例子。我们能够将该模型融入产品场景中,比如在 Google 地图产品中实现“地图问答”。但支撑它的许多技术——语音技术、模型、智能——都是一项统一的工作,因此我认为 AI 时代为我们提供了一种新的思考方式,而且不仅限于 Google,随着时间的推移,在整个 Alphabet 范围内也是如此。这个时代之所以如此独特而强大,是因为你可以在研发和基础设施上投入巨资,开发出一项技术,然后将其应用到所有这些领域——显然是在对用户有用的场景中——但底层技术平台是通用的。这其中蕴含着大量的意图,等等。
你必须为创新留出空间,因此要允许团队在边缘地带推出一些新功能。有时你之后会进行整合。以 NotebookLM 为例。笔记本功能现在出现在 Gemini 中,它实际上就是作为笔记本的项目。你可以在 Gemini 中创建一个笔记本,然后去 NotebookLM,你会看到同样的笔记本,反之亦然。所以这是一个先创新、后整合的例子。
我昨天观看了主题演讲,看到了 Google 的许多意图和自信:“我们拥有这项核心技术。我们可以用多种方式来表达它。它本质上仍然是 Google 的风格。”有很多产品,很多关于 Gemini 的词汇。我会把它们都弄明白的,我保证。
我想将这与……大概三四年前的ChatGPT时刻做个对比。当时所有人都担心谷歌会如何应对。OpenAI能否横空出世,抢走我们的市场份额和搜索业务?从那时到现在,你们改变了谷歌。你们重组了它。领导层也出现了新面孔。请为我梳理一下其中的关联。你是如何思考“我需要真正改变公司的运作方式”,并应对当时的竞争局面,从而走到今天这一步的?
这是个很好的问题。我一直将那个时刻铭记于心。对外界来说,这很难传达,但我让公司全面转向了AI优先。我们拥有所有必要的要素,所以在某种程度上,我觉得奥弗顿窗口已经改变了。人们采用这些技术的速度超出了我们的预期。对我来说,这是一种通过产品来真正表达自我的方式,但我意识到我们必须为此进行组织调整。回到我之前的观点,我意识到我们需要一个核心模型和一个核心基础设施团队,来支撑我们在谷歌所做的所有事情。我最初投入了大量精力来建立这个体系。
为了组建一个统一的AI团队,我们拥有世界一流的研究团队,即Brain团队和DeepMind团队,并将它们合并为Google DeepMind。这比听起来要困难得多,因为这就像是在说:“把斯坦福大学和麻省理工学院合并,从中创建一个院系或一所大学。”所以,我认为我们在这方面做得很好。当时,我还与现任AI基础设施高级副总裁的Amin Vahdat一起,建立了一个集中的基础设施团队,这带来了巨大的回报。另一个演变是,我们意识到需要一位首席AI架构师来为整个谷歌设计这项技术,而Koray Kavukcuoglu也承担了这个角色。这些都是重要的变革。
搜索需要更快地推进,而搜索业务此前由多位负责人分管,因此我们将其统一交由伊丽莎白·里德管理,由尼克·福克斯负责整体领域,乔什·伍德沃德协助我们的实验室产品,随后参与 Gemini 工作并推动创新。公司还有其他杰出的领导者,比如负责所有运营事务的菲利普·辛德勒。因此,这是退后一步,从端到端角度思考组织架构,确保我们为当前需要公司更快运转的时刻做好充分准备,这意味着我们必须更快地做出决策。
我设立了每周一次的新产品评审会。这些是 AI 产品评审,确保我们有意识地决定如何应用这项技术、在哪些场景应用,并亲自审查所有内容——凡是涉及 AI、且将交付给用户的产品,都必须经过这一流程。我会直接与相关负责人员沟通。
另一个《解码器》栏目中我会问所有人的问题是关于决策的。你描述了许多重大决策,其中一些在调整人员时令人感到不适。你是如何做决策的?你的决策框架是什么?
我的框架中很重要的一部分是,随着时间推移我认识到,真正具有重大影响的决策少之又少,大多数决策并非如此。更重要的是你要做出决策,因为这决定了组织的运转速度。你越能做出这些决策并推动公司前进,整体状况通常就越好。
当然,有些决策——比如合并并组建 Google DeepMind——影响更为深远,你需要花时间仔细斟酌。但大多数决策的关键在于果断执行。你越能这样做,就越能逐渐形成模式识别能力,因为你之前遇到过类似的问题。因此,我认为应该依赖这种经验,区分信号与噪音——信号意味着这是一个真正重要的决策,需要认真权衡;而有些决策看似重大,实则只是你需要采取的常规行动。
放眼整个行业,你在大型科技公司的同行们有着我平生听过最天马行空的组织架构设想。我认为 Meta 希望借助智能体的力量,让 50 名工程师向同一位经理汇报。Block 的 Jack Dorsey 则想让全部 6000 名员工直接向他汇报。你是否也有类似的想法,认为应该用 AI 创造出一些前所未有的、最疯狂的组织架构?
领导者和人才至关重要。而且这取决于具体情况。有些公司的产品线要窄得多,因此不同的架构可能奏效。当你运营着像 Google Cloud 这样规模庞大的业务时,有一位 CEO 掌舵非常重要。我们大规模地服务着全球所有顶级企业,那么该如何为此进行组织架构呢?优秀的领导者最终会发挥巨大作用,比如我们有 Thomas Kurian 在那里。我确实在思考这个问题。
但我真正思考的是,我们如何更有效地利用 AI。我们在内部已经看到了转变,尤其是在我们的开发者群体中,我们已经从使用 AI 工具辅助编码,过渡到一部分工程师越来越多地有效指挥 AI 智能体团队。这些转变正在进行中,并且将超越工程领域,扩展到组织的其他部门。这已经在发生了。就连我们在 Gemini Spark 中所做的工作,也是为了将这种超能力交到消费者手中,以及这些智能体工作流所能实现的功能等等。
我更专注于确保我们真正以原生方式部署这种能力,并且它能良好运行,因为对我们来说,这不仅仅是让公司更高效,更关乎我们提供给其他人的产品。我以完全不同的视角来看待这件事。我们内部的做法,正是我们提供给外部用户的东西。我们在内部使用 Antigravity。这也是我们对外提供的东西。因此,Antigravity 中的智能体正是我们的开发者所使用的,而这正是我们试图推向外部的东西。它因此多了一个维度。
《Decoder》的听众最想让我开始问 CEO 们的问题……我就直截了当地问了。AI 距离取代你作为 CEO 还有多远?
我只是觉得CEO这份工作没那么复杂。在某些方面,我认为它在决策层面会变得非常、非常有帮助。我开玩笑说——半开玩笑地说——我不得不花大量时间分配算力。然后我就想,“嗯,从长远来看,AI似乎会做出更理性的选择,”因为我在处理这类流程时,要应对很多申诉和情绪因素。
我在各处看到的——这或许与我的想法略有不同——是如果运用得当,这些工具将让我们在所有工作中都提升到新的水平。这并不意味着你不再做以前做的事。而是你会从一个更高的起点出发。我不知道电子表格刚在企业推广时我是否在场。我得回想一下,在那之前人们是怎么做所有这些财务分析的?我敢肯定,在三到四年的时间里,它发生了根本性的变化,而我们也逐渐习惯了。
我认为智能体等等就是它的一个版本。这并不意味着你不再计划生日派对。假设你在计划一次旅行。也许你实际上是在花时间思考你真正想用时间做什么,而不是去查开放时间、如何买票等等。在我看来,它把一切都提升到了不同的基础层面。
我想问问你关于这个和智能体的事。其中一些演示非常吸引人。搜索将为每个人构建定制软件这个想法,在软件工程领域似乎只是一个初步印象。这个想法是,你向计算机提问,而回应则是它为你制作一个能帮你找到答案的软件。我对这个想法很着迷,但这从根本上改变了搜索。
再看看 Gemini Spark,这是你在云端的智能体平台,你可以对它说:“帮我去订几张票”,然后 Spark 可能会四处运作,帮你订好票或完成某项任务。此外还有 Antigravity,这是智能体编程平台。总体来看,每年 AI 都会出现一种新范式。先是有了大语言模型,然后我们可能一起对某些大语言模型进行改造,接着是推理,现在又到了智能体阶段。这是基础架构,还是说未来还会有另一场范式转变?
这是个好问题。我们正在搭建大部分基础模块。从根本上说,能够进行推理、使用工具和编写代码,这本身就非常接近拥有智能和推理能力——能够规划、能够查找信息、使用工具,并且如果需要的话,还能在此基础上构建东西。你正在铺设所有的基础原语。Antigravity 是为开发者准备的,但 Antigravity 引擎及其框架现在已经内置到 Gemini 中了。而 Spark 只是 Gemini 的一种模式。随着时间的推移,它会成为一个功能。我们正在对它进行定位,但它只是 Gemini 中的一个选项卡。
所以你们正在引入那个智能体框架。用户不需要去考虑它。开发者会理解它。随着时间的推移,在 Spark 中,他们可以编写出功能强大的东西。但作为用户,你可能会构建某些东西、创作内容、规划旅行,而所有这些都在后台运行。
我们正在铺设大量让智能体端到端运行所需的基础原语,更重要的是,让 AI 能够正常工作。我们一直以来都怀有 Google Assistant 的长期愿景,尝试过各种形式,却未能完全做好,而现在我们比以往任何时候都更接近实现这一承诺。我们还没有完全实现它,但这段旅程,我认为现在比以往任何时候都更接近终点。
我审视了所有这些产品,它们看起来确实应该融合。你们有了新的智能搜索框,我当然想更详细地聊聊搜索。但你看那个搜索框,再看看比如能帮你生成应用的 Canvas。你正在筹备婚礼,它就能直接为你生成一个帮你规划旅行或婚礼的应用。然后还有能自主执行任务的 Spark。我昨天跟人聊到这个,很明显这些应该整合成一个产品。
会的。我前面举了 Notebook 的例子,比如你在创建 Notebook……但 Notebook 到底是什么?本质上,你是把所有你需要的上下文放在一个地方,然后基于它来工作。它就像人们一直使用的文件夹,而 Notebook 应该成为你使用的所有 Google 产品中一个统一的底层概念。我就是这么看待智能体的。它不应该有区别。在创新的最初阶段,你是在创造能力。各个团队在尝试它,但对用户来说,长远来看,如果你发起一个“规划旅行”的任务,它应该能在不同场景下协同工作,我是这么理解的。你说得对。
Google 搜索有一个非常重要的特质——无论过去多少年,甚至几十年,它一直是人们心目中的真相来源。去 Google 一下,你就能得到答案,而且这个答案对你我来说通常是一样的,这一直是一个非常重要的理念。我认为,这已经成为了文化中的一个固定元素。也许在所有公司中,Google 是最后一家还在坚持说“我会直接告诉你真相”的公司。
好吧,但现在我们要让搜索框无限个性化,也要让搜索体验无限个性化。我们每个人对同一个查询都会得到不同的答案。甚至,根据我们问的是什么、我们的个人背景是什么、Google 掌握了多少数据,我们看到的界面都可能不同。
你对此有深刻的思考吗?你在多大程度上会动摇大多数人在互联网上体验到的最后一个共同的真相来源?
你看,有很多因素是我们完全无法控制的——如今人们拥有的信息来源比以往任何时候都更加广泛。人们从如此众多的不同渠道获取内容。但在谷歌的范畴内,我仍然认为我们深切关注的是,这应当成为一个知识与信息的来源。客观体验和主观体验是并存的。美国首都是哪里?这个问题不会为任何人定制答案。这些都是客观事物。“帮我规划一趟去蒙特利尔的愉快周末旅行”——自然,答案不必对每个人都相同。这其中存在一个连续的光谱。
我们对此非常重视。对于某些类别的信息,我们仍然会锚定权威信息,尽可能呈现客观的视角。如果是与健康相关的查询,我们自然会倾向于展示比“哪个更好?我该去买哪个?”这类问题更具权威性的答案。
我能给你看一个搜索结果吗?
当然可以。
几年前,我给你看过一个搜索结果。这个结果我已经追踪了好几年。
我一直很喜欢这个。在数以万亿计的查询中……
是的。嗯,这个是我的最爱之一。
我们有一套非常科学、统计化的方法来处理这件事。
我认为这很重要,我想谈谈消费者可能如何体验这些产品。所以这是我经常做的一个搜索:“最佳 Chromebook”。我就直接展示给你看。就是这个。
首先出现的是一个 AI 概览。它非常自信地告诉你答案,然后是一堆赞助商框。接下来让我在意的是,就在这下面,我认为结果是 Reddit,并且它显示了 Reddit 上的一个置顶结果。实际上,这个答案与 AI 概览给出的不同。然后是《纽约时报》,它又给出了一个不同的答案。
你往下滚动页面时会想:“AI 概览告诉我一件事,第一个自然搜索结果在页面相当靠下的位置,而且所有这些答案都各不相同。”我理解你刚才说的客观结果和主观结果的区别。“我该买哪款笔记本电脑”这个问题,正好处于这两者之间的某个位置。我只是好奇,你认为如今在 AI 模式下,消费者的这种体验如何,以及你认为它未来应该走向何方。
说得非常清楚,在 AIO 领域,我们使用的是 AI 模式。我们负责组织和提供上下文,但全程都有来源标注,所以你仍然是以不同方式呈现原生内容。你会看到链接和来源,但同时也附带了观点,这正是你刚才谈到的。
其中一部分会与用户进行迭代。我们在搜索领域发现的一大优势是,用户满意度很容易衡量。25 年来,我们学会了如何将用户幸福感、用户满意度与产品品质的提升进行关联性衡量,而不是追求短期效果。这就是我们进行长期研究的原因。如果我们在任何体验上出了问题,数据指标会立刻反映出来,我们就会及时修正。我们引以为傲的是能够长期追踪这些指标——无论是用户参与度、会话次数、回访话题的频率,还是用户跳出次数。这是一种非常非常精细的观察方式。在某些类似领域,这种体验还会持续演进。
你认为目前的体验好吗?
对于你刚才展示的那个特定查询来说,它可能比应有的程度更带主观倾向。这是我作为用户的直观感受。我的说法是,在一个快速演进的领域里,这恰恰是改进的空间,但我预计产品本身会逐步完善。我的直觉是:“哦,这主观倾向太强了。” 也有一定可能性这是针对你个人的个性化结果。你可能正在以一种独特的个性化方式测试它。不过,那个查询之所以可能不完全具有代表性,是因为我了解你审查所有这些内容的方式。你有可能属于那 0.0001% 的用户——
这正是我问你关于“无限个性化结果”的原因,对吧?同时我也在问体验是否良好,因为我敢打赌,绝大多数用户一直都在体验 Google 搜索中的 AI。他们遇到过那种被强制切换到 AI 模式的情况。一方面有你可以衡量的用户满意度数据,另一方面还有公众对 AI 的整体感受。
我认为在“用户数量在增长,我们接近十亿用户,人们正在体验的免费产品有多好”与民意调查数据之间,存在着相当明显的鸿沟。年轻人不喜欢AI。这一点客观得不能再客观了。你可以去问他们,他们会以可衡量的方式告诉你,他们不喜欢它。
谷歌前CEO埃里克·施密特在一次大学毕业典礼演讲中被喝倒彩。七成美国人反对建设数据中心。人们的产品体验与他们对该技术的感受之间存在某种差距。你认为你能弥合这个差距吗?你认为这些产品足够好吗?
这是一个非常深刻的话题,而你把这两件事联系在了一起。AI是人类将要面对的最深刻的技术。它正以非常快的速度发展。我认为人类并没有进化到能够处理如此多的变化,尤其是过去几年的变化速度极其惊人。特别是考虑到他们听到的所有信息,人们正试图从个人生活的角度去理解未来,包括它在经济层面意味着什么等等。
人们对这项技术感到焦虑,这完全说得通,我们应该非常敏锐地意识到这一点。这是一个重要的话题,而且比正在发生的具体方面更广泛、更宏大。人们并不总是直接把这两件事联系起来。在某些情况下,是的,它们确实以某种方式相关联。
人们在各种产品中体验这些模型的免费版本。他们打开社交媒体信息流,看到的是垃圾内容。他们看到关于所有这些事情的新闻标题。这些工具就直接摆在他们面前。Gemini的闪光标志出现在所有谷歌产品中,无论你是否要求它出现。然后我确实认为你会把它联系起来:“他们需要大量电力,也许我的电费会涨。也许所有的工作都会消失。”这相当可怕,我不知道价值交换是否对等。
这些都是值得研究的好方向。你过于聚焦具体现象,而我是在拓宽视角,指出那可能只是部分解释。我确实认为还有其他更廉价的因素在起作用。
你认为这仅仅是营销问题吗?我听过你的同行说,AI 只是存在营销问题。
不,我不这么认为。这正是我要表达的观点。实际上我是在反驳这种看法。我觉得人们对此产生担忧是合情合理的,这在我看来很自然。人们都在谈论 AI 可能导致大量工作岗位消失,你凭什么不感到焦虑呢?我认为这些是我们作为社会必须应对的更深层次问题。是的,在产品层面也存在对 AI 垃圾内容的担忧,这些都没错。我只是想指出,这是一个多层次的问题。但我并不认为数据中心引发的焦虑情绪,全都直接源于你在某个产品中的具体体验或类似单一因素。这就是我想表达的全部意思,对吧?这个问题比那更广泛、更重大。
现在确实充斥着大量 AI 垃圾内容,我深有体会。在技术早期阶段,加上现有的竞争态势,很多东西都被仓促推出。但我们也从实证中看到,人们正在非常深入地使用这些产品。如果你去一个 Waymo 尚未覆盖的地方,随机采访人们对自动驾驶汽车的看法,得到的民意调查结果与他们实际使用这些汽车时的感受截然不同。技术也会经历这样的过程。顺便说一句,如果你问人们对互联网的看法,得到的评价也相当负面。但它已成为我们生活的基石,我们必须去适应它。所有这些现象都在同时发生。
这是一个复杂的话题。在我看来,人们似乎担心能源价格上涨,如果是这样,他们希望确保人工智能不会加剧这个问题,这是合理的担忧。作为行业,我们有责任确保,在建设数据中心时,我们能做些什么来避免助长这个问题?我认为这是我们的责任,不仅仅是我们。政府方面,两党对此也存在一些担忧。例如,我们都签署了一份关于费率缴纳人的承诺书,做出了一系列承诺。也许还需要做更多工作。所有这些都相辅相成。讨论技能培训、劳动力适应等话题也很重要。我们正在推动社会快速发生巨大变革。这些最终也会成为非常重要的话题。
在这些层面都存在担忧,而且我预计随着我们向前发展,这些担忧会变得更有意义。多年前我曾说过:“这比火或电的影响更深远”,我们一直是这样认为的。或者想想深度伪造,你如何判断某件事是真是假?这些模型在模拟现实方面越来越强。这就是我们如此努力工作的原因。我们将其开源,汇聚了众多合作伙伴,看到行业在这样的议题上合作,我感到非常欣慰。网络安全是另一个很好的例子。这些都是切实存在的担忧。
作为行业,我们需要做得更多。政府将发挥更强的作用,公众也需要参与进来。在民主国家,你不能让一项影响最深远的科技在公众没有合理发言权的情况下推向世界。经历这个阶段非常重要,这是我们学习如何适应的方式。
我的观点是,产品本身就在做营销工作。这是我的主张。我仍在等待一款能实现这一点的面向消费者的杀手级应用。我认为我们已经有了面向企业的杀手级应用。
有一点,我有时会在 Gemini 中经历健康方面的探索。对我来说,这感觉不仅仅是一款杀手级应用,比我以前做过的任何事情都要好。人们也正在经历这样的体验。
我想谈谈网络,以及 Gemini 中的健康旅程功能,这需要网络上存在丰富的健康信息数据集才能实现。你们在用 YouTube 视频训练 Gemini,对吧?Veo 需要 YouTube 生态系统才能运作、才能产生成果、才能创作新作品。多年来,你我一直讨论我称之为“Google 归零”的概念,即你们将停止向网络输送流量。你一直不同意我的看法,认为这不会发生。
非常不同意。过去这么多年都没有发生。
好吧,我给你读一段引述。这次不是我说的,也不是我引导他说的。康泰纳仕的 CEO 罗杰·林奇上周接受了 TBPN 的采访,他说:“每年我们的搜索流量下降幅度都超过预期,所以去年我告诉团队:‘假设没有搜索。你们必须按照搜索流量为零来规划业务。’”
这就是“Google 归零”。康泰纳仕在说:“我们假设搜索流量将归零。”对此你怎么看?世界上最大、最具标志性的出版商之一说:“我不能再依赖这个了。”
听着,首先,信息生态系统远不止 Google,范围要广得多。我们在数据中看到了这一点,你在任何地方都能看到。所以,如果任何一家出版商在过去 10 年里……我会看看 The Verge,想想你当初接手时是什么样子,自那以后它发生了多大的演变,你们制作的内容类型,你们在哪些地方发布这些内容,用户又是如何找到你们的。这个领域极其动态,所以在我看来,每家出版商都在适应这个新世界,这是合情合理的。
我们正在适应不断变化的世界以及用户消费技术的方式。当世界从网络转向移动端时,我们就不得不这样做。现在,我们正从移动端的世界,转向人们进行持续对话、与这些产品聊天、与它们交谈、通过语音和多种不同形态的设备来消费内容的世界。
人们正在表达对不同类型内容的偏好。他们想要用户生成的内容,想要播客,想要这类东西。自始至终,我们都坚定致力于既满足用户期望,又把他们与网络上的内容连接起来。就在过去一年里,甚至自从我们推出这些功能以来,我们回过头去增加了更多链接。另一个行为正在发生变化的领域是,许多出版商(这完全合理)正在考虑订阅模式。
当然。但我想说的是,康泰纳仕(Condé Nast)正在表态:“鉴于我们看到的趋势,我们将假设我们的搜索流量为零。”他们应该这样假设吗?
听着,我一直认为……人们更了解自己的业务……我的意思是,我无法告诉这样一家标志性的出版商他们应该如何思考自己的业务或规划。如果他们制作的是高质量且人们喜欢的内容,我期望我们的产品能够反映这一点。这一点我可以向他们承诺。
但我认为,在这场演变中,我们比任何其他公司都更加努力地确保人们能够建立连接,我们计划在搜索和 Gemini 中做到这一点,而这仍然支撑着我们的大部分工作。但演变确实存在。随着技术的进步,低质量的点击会被过滤掉。这是我们看到的自然演变。我们在指标中看到了这一点。无效点击正在减少。这些都是动态变化。
人们正在获取更广泛的信息来源,而生产信息的人也比以往任何时候都多。这块蛋糕正在变大。所有这些动态都在发生。这是一个复杂的生态系统,但我们的承诺是确保我们能够反映内容的广度和多样性,我们确实认为人们最终希望连接到这些来源,但我们正努力在这些时刻满足他们的需求,而人们带着截然不同的意图和不同的场景而来。
我们做的一个小功能——但我认为非常重要——就是如果你订阅了某个内容,我们会将其反映为你的偏好来源。但这是一项新变化,我们之前没有这个功能。我们正在适应出版商越来越多地转向订阅模式这一现实。
出版商和 YouTube 创作者,如果他们选择退出训练,是否还能在搜索结果中被呈现?
这是一个更广泛的话题。法律和法规都需要演进。法院也必须介入。保护版权很重要,保护合理使用也很重要。这些都是会通过这个过程动态演进的架构。
但你愿意和 YouTube 创作者打一堆官司吗?你们在英国已经和出版商有官司了。那场官司中的言辞越来越激烈。谷歌曾表示,拟议的解决方案是"搭便车宪章"。每年新闻媒体协会都会给我发一段话让我读给你听,他们说:"谷歌称我们为搭便车者,这显然很荒谬。这是基本的供应链经济学。如果价值真的全在谷歌这边,他们大可以允许出版商选择退出。"
你想在 YouTube 上和一众创作者就选择退出问题陷入同样的争斗吗?
你看,我们一直在——作为 Gemini 开发的一部分……
我们确实通过 Google-Extended 提供了新的退出选项,并且正在与出版商进行对话。我们会听取反馈,并随着时间的推移找出合理的方案。显然,我们并不是这个大生态中的唯一参与者。我们也在努力推出与其他产品有竞争力的产品。所有出版商也会写文章说这个产品不太好。所以这比表面看起来要复杂得多。
你花了更多时间思考网络、网络的健康以及网络的必要性。请为我描绘一下,在智能体搜索的世界里,一个健康的网络应该是什么样子。
我长期以来一直持有的一个论点——而且我确实看到它正在逐渐显现——就是过去一年到一年半的时间里,我又开始更多地使用网络了。所有这些 AI 体验让网络重新回归。曾有一段时间,感觉好像……但我始终认为网络会充满活力。事实上,我每年都在论证网络会充满活力,今天我也依然这么认为。网络在不断进化。我从未见过像网络这样充满活力的东西,这也是为什么能参与这场进化是如此荣幸。
我关注智能体,那是网络的下一次进化,我们将要面对它,而且我认为它会深刻地改变网络。关于什么可以、什么不可以,会有很多争论,但人们想要发布信息,想要与他人建立联系。人们渴望连接。人们并不想生活在一个孤立的、与世隔绝的世界里。那不符合人类体验的现实。我认为网络将一如既往地扮演核心角色。事实上,我们昨天宣布的通用商务协议(Universal Commerce Protocol),我认为人们有些低估了它的影响。
实际上,我能把这两件事放在一起对比吗?有很多重磅发布,关于新产品、新功能,以及你可以使用的智能体工具,还有 UCP,亚马逊和沃尔玛等都在说:“我们将采用我们正在构建的新购物标准”,所有这些都非常具体实在。
然后 I/O 大会以 DeepMind 首席执行官戴密斯·哈萨比斯的出场收尾,他说了一句话,让我一直念念不忘。他说:“谷歌的前沿研究和产品将帮助释放 AGI 的巨大潜力,造福整个世界。当我们回首这段时期时,我想我们会意识到,我们当时正站在奇点的山麓。”
你能告诉我,站在“奇点的山麓”是什么意思吗?
戴密斯和我曾就这个话题进行过深入的长谈。在这个语境下,AGI 的到来就是他心目中的奇点。
你对 AGI 有定义吗?你们讨论过吗?你们达成一致了吗?
我们对此讨论很多。我认为戴密斯和我在思考问题的方式上非常接近。AGI 有一个更严格的定义,即它必须能够更全面地执行广泛的任务,包括认知任务,并且达到可比较的水平。我们最终会以公司的形式将其推出,我们正在为此努力。但这就是他在这个语境下所谈论的内容。
顺便说一句,我认为我们有必要理解这项技术正在飞速发展。今天晚些时候,我将花时间与我们的 AI 研究人员交流,不仅是我们公司的,也包括前沿实验室的。大家广泛共识是,这项技术,即 AGI……人们可能会争论它是否会在三年内到来,但这项技术迟早会到来。传达这一点更为重要,因为——回到我们对话的前面部分——我们整个社会理解它并尽可能做好准备,这一点至关重要。
也许在我们第一次谈论 AI 时,我就问过你这个问题。我问过你,语言是否就是智能。而这里的发展路径是,我们正在大语言模型之上叠加越来越多的层次。我们正在做更长的推理链,我们正在构建框架,我们正在做所有这些事情,但核心技术仍然是 Transformer 架构。它仍然是谷歌很久以前发明的东西。大语言模型能带你走向 AGI 吗?这条路径清晰吗?
过去三年的发展轨迹令人难以置信。如今的大语言模型在许多方面也已经进化了。我们也在不断进化它。对我来说,这就像在问,计算机能带我们走向——?冯·诺依曼架构仍然是当今大多数计算机的驱动力,但他可能认不出我们现代的 TPU Pod。或者他也许能认出来。它们之间仍然有很多共同点。底层技术在持续深刻地进化。在我看来,我们每年都有重大突破。我的意思是,你刚刚看到我们在 Antigravity 演示了通过提示词来创建一个操作系统的能力。
谷歌能够制造新的操作系统,这是非常危险的。
我们得确保不要在生成内容时超出模型 token 上限……这点我承认。说得没错,但这恰恰是这些工具的强大之处,对吧?世界上顶尖的数学家、顶尖的物理学家都在与这些工具互动,并以重要的方式使用它们。但这些工具能否从根本上自主做出全新的科学发现?目前还不行。
它的进步程度令人惊叹。我确实认为它还需要经历重要的演进过程,而且外界对于要迈出下一步需要具备多少对世界的真正理解,存在各种强烈的观点。我相当乐观,相信我们会继续取得大量进展。
你的时间线是怎样的?是三年,还是五年,达到 AGI?你目前怎么看?
我一直是这样回答的:我认为那个时间线并不重要,因为进步的速度意味着你正在以一种深刻的方式与越来越智能的系统打交道。所以我对这个问题的回答是,三年后,无论你我还是否称之为 AGI,那都不重要,因为它会变得非常非常强大,我们必须为此做好准备。
Sundar,这次访谈很棒。再次感谢你抽出时间。
好的,谢谢你,Nilay。这是我的荣幸。
Today, I’m talking with Google and Alphabet CEO Sundar Pichai, in a conversation we recorded just after the Google I/O developer conference. This is the fifth year Sundar and I have sat down after I/O, and it’s become one of my favorite Decoder traditions.
There’s always a lot of news at I/O, and this year was no exception — Google has powerful new Gemini models, it’s putting AI agents in everything, and it’s making huge changes to Search on both the web and YouTube that will once again reshape the information ecosystem.
That’s a lot to talk about, and Sundar and I got into all of it. But I also realized it’s been a long time since I’d asked Sundar the Decoder questions about structure and decision making, so I started there. You’ll hear Sundar say he realized he needed to rethink how Google worked a few years ago in response to ChatGPT, and he made a lot of executive changes and big decisions to get the company in a more aggressive posture.
Of course, we also talked about all those search changes, and how it seems obvious that the real future of Google Search is bringing things like the new intelligent search box together with the company’s new Gemini Spark agent platform. That way, searches can set off tasks, not just deliver results. That’s exciting, but it seems likely to yet again change the dynamics of the open web.
If you’re a Decoder listener, you’ll know that I coined the term Google Zero a few years ago — that’s the idea that Google traffic to websites would fall to zero as the company answered more and more queries directly on the search results page. That’s gone from an idea Sundar batted away in previous interviews to something the entire media industry is grappling with. Even the CEOs of major publishers like Condé Nast are now publicly saying they’re planning for a world of zero search traffic from now on.
Google is also training its models on YouTube videos, and changing YouTube search to summarize and index videos so you get dropped right into the relevant parts. That’s sure to cause some creator angst, so I asked Sundar if he’s ready to fight the same battles with YouTubers as he currently is with publishers.
Finally, I asked Sundar about Google DeepMind CEO Demis Hassbis ending the I/O keynote by saying we’re “at the foothills of the singularity.” It’s no surprise that Sundar agrees with Demis, but his thoughts on the timeline to AGI are worth paying attention to.
Like I said, it’s one of my favorite episodes to do every year, because Sundar is always game to actually take the questions — and even look at search results on my phone with me. I think you’re really going to like this year’s conversation.
Okay: Sundar Pichai, CEO of Alphabet and Google. Here we go.
This interview has been lightly edited for length and clarity.
Sundar Pichai, you’re the CEO of Alphabet and of Google. Welcome back to Decoder.
It’s great to be here. Nice to see you again, Nilay.
This is one of my favorite yearly conversations. I think we’ve done it at I/O now almost five times.
Wow. I didn’t quite realize it’s been five times, but I enjoy it. Thanks again.
I want to start with a little bit of a lightning round. I was thinking about this. We’ve talked a lot. We always get deep into the weeds of the web and search and big, heady ideas, and I realize I have not asked you the Decoder questions in quite some time.
I was just looking back at our previous conversations, and Google itself, and you’ve made quite a lot of changes to Google. I think a number of your direct reports have changed over time. You’ve obviously restructured DeepMind, platforms and devices, and Android. Tell me how Google is structured right now.
Okay. It is Google and Alphabet. Obviously we have Alphabet as well, but broadly I think about it as there are three main businesses in Google: Search, YouTube, and Google Cloud. There are enormous platforms we run, which is Android, Chrome, and the whole area to do with it. And powering it all is all these important technology areas, which is AI and our infrastructure work. And then you have the functions to go with it.
But at a high level, you can think of it as Search, YouTube, Google Cloud, and then our big computing platforms. Those are the main groups, and obviously powered by Google DeepMind and our infrastructure teams. That’s one simple way to get a mental model around it. And of course, we have other bets beyond that, Waymo being the most prominent of them all, but there are many, many other bets, like Isomorphic Labs and so on.
I want to stay focused on the Google of it. I feel like we could do an entire hour on Alphabet and how that’s structured and how that works as a public company with many bets. But just to stay focused on Google for one second, the knock on Google historically is this is a company that ships lots and lots of products. You can’t sell lots of products. There’s not tons of focus. There are thousands of names of different products that are overlapping in different ways.
Where that comes from, at least in my view, is that you do have these big infrastructure bets. You have all these capabilities, and the people running the businesses can use those capabilities to spin up products. And there’s maybe not a lot of overlap or central planning like, “Did we launch two of the same thing?” How do you resolve that tension? It does seem like Google has gotten a little more focused, but that is the company’s culture: “We’re going to make a lot of bets and see which ones work.” How does that resolve for you?
There’s a lot of intent in what we do too. I think it’s not an accident we have 13 products with a billion users each, and we’ve been committed to those products longer term. You can go back and think about when Gmail launched or Maps launched or Google Docs launched or Search launched or Chrome launched. We’ve been deep and consistent in many, many areas over a long period of time as well.
One way I’ve internalized it in the AI moment is for the first time, we have such a common infrastructure powering all of them with our Gemini models and the underlying AI infrastructure. So we are more able to, with intent, do things which cut across things. Personal intelligence is a great example of it. It’s one effort. Users get a choice to turn it on in each of the products, but it’s built with one common infrastructure so that it works consistently across our products.
The underlying Gemini model itself is an example of it. We are able to bring that model in the context of the products, like Ask Maps in the context of the Maps product. But a lot of the technology powering it — the voice tech, the model, the intelligence — is all one work, which is why I think the AI moment offers us a new way to think about it, and not just across Google, but across Alphabet too over time. What makes this moment so uniquely powerful is that you can invest so much in R&D and infrastructure and develop a technology, which then you can apply across all these areas, obviously in a context in which they are useful for users, but the underlying technology platform is common. There’s a lot of intent that way and so on.
You have to give room for innovation, so allowing room for innovation where teams on the margin are able to ship some new features. Sometimes you later work to harmonize them. Take NotebookLM. Notebooks are now showing up in Gemini, and it’s effectively projects as Notebooks. And you can create a Notebook in Gemini, you can go to NotebookLM, you will see the same Notebooks, vice-versa. So that’s an example of where you innovate it first, and then you’re harmonizing later.
I was watching the keynote yesterday and I saw a lot of intent and confidence from Google: “We have this core technology. We can express it in lots of ways. It’s still essentially Google-y.” There are lots of products, lots of Gemini words. I’m going to figure them all out, I promise.
I would contrast that with… I don’t know, three, four years ago when there was the ChatGPT moment, everyone worried about what Google would do. Could OpenAI show up and take your market share and search away? Between that and now, you have changed Google. You have restructured it. There are new people in leadership roles. Connect those dots for me. How did you think about, “I need to actually change how the company works,” with the competitive moment you were in that got you here?
That’s a great question. I always internalized that moment. It was tough to convey it outside, but I pivoted the company to be AI-first. We had all the ingredients, so in some ways I felt like the Overton window had changed. People were adopting these technologies faster than we had expected. To me it was a way to go and actually express ourselves through our products, but I realized we had to organize ourselves for it. And going back to my earlier point, I realized we need a core model and a core infrastructure team to power everything we are doing across Google. A lot of my initial energy was to go set that up.
To get one AI team, we had world-class research teams in Brain and DeepMind and brought those together as Google DeepMind, which was harder than it sounds because it’s like saying, “Go put Stanford and MIT together and create a department out of it or a university out of it.” So I think we’re doing that well. At that time I also set up with Amin Vahdat, who’s now our SVP of AI infrastructure, a centralized infrastructure team, which has paid great dividends. Another evolution was realizing we need a chief AI architect to architect this technology across Google, and Koray Kavukcuoglu took on that role as well. Those were important changes.
Search needed to move faster, and Search was split across many leaders, so we put it under Elizabeth Reid, with Nick Fox being responsible for the overall area, Josh Woodward coming to help with our Labs product and working on Gemini later and driving innovation. I have other extraordinary leaders in the company as well, leaders like Philipp Schindler who runs all our operations and so on. So it is stepping back, and thinking end to end about the structure and making sure we are set up well for this moment where we need to move faster as a company, which means we need to make faster decisions.
I set up these new product reviews once a week. They were AI product reviews, making sure we are intentional about how we apply this technology, where we apply it, and to review everything firsthand, that anything to do with AI, which we were shipping to users, went through that channel. I spent time directly with whoever was working on it.
The other Decoder question I ask everybody is about decisions. You’re describing a lot of big decisions, some of them uncomfortable as you change people around. How do you make decisions? What’s your framework?
A big part of my framework is over time understanding that there are very, very few decisions which are really consequential, and most decisions aren’t. What matters much more is that you make the decision, because that’s what determines the velocity of an organization. The more you’re able to make those decisions and keep the company moving forward, you’re generally better off.
Of course, there are a few decisions like combining and setting up Google DeepMind that are more consequential, and you want to take your time deliberating and doing it. But a lot of decision-making is about just making them. The more you’re able to do that, the more you do develop over time some pattern matching and you’ve seen a version of the problem before. So I think it’s good to rely on that and separate the signal from the noise so that the signal is that this is a really important decision and you want to really deliberate around it versus it may look big, but it is more a normal course of action you need to take.
Looking around the industry, your peers in Big Tech have some of the wildest org chart ideas I’ve ever heard in my entire life. I think Meta wants to have 50 engineers report to a single manager with the power of agents. Jack Dorsey at Block wants all 6,000 people to report to him. Are you having similar thoughts that you should invent some of the craziest org charts with AI ever?
Leaders and people are incredibly important. And it depends. Some companies have a much narrower suite of products, and so different structures may work. When you’re running something at the scale of Google Cloud, it’s important that there is a CEO in charge. We are serving all the top enterprises in the world at a scale, and so how do you set up for that? Great leaders end up mattering a lot, like we have Thomas Kurian there. I do think about it.
But what I do think about it is how we are using AI more effectively, and we’ve seen the transition internally, particularly amongst our developers where we have transitioned from using AI tools to assist coding to them, a portion of the engineers directing teams of agents effectively more and more. Those are transitions underway, and that will flow beyond just engineering into the rest of the organization. It’s already happening. Even the work we are doing in Gemini Spark is to put that superpower in the hands of consumers, and what you can do with these agentic workflows, et cetera.
I’m more focused on making sure we are actually deploying that capability in a native way and that it’s working well, because for us it’s more than just making the company efficient because it’s the products we provide to others. I look at it with a very different lens. How we do it internally is what we are giving to users outside. We use Antigravity internally. That’s what we are providing outside. So the agents in Antigravity are what our developers are using, and so that’s what we are trying to put outside. It has that extra dimension to it.
The number one question Decoder listeners want me to start asking CEOs… I’ll just ask it straightforwardly. How close is AI to replacing you as the CEO?
I just think the CEO job is not that complicated. There are aspects of it where I think it’s going to be very, very helpful in terms of decision-making. I joke around that — partially joke around — that I have to spend a lot of time allocating compute. And I’m like, “Well, that seems like the AI is going to make more rational choices over time,” because I deal with a lot of appeals and emotions as part of working through a process like that.
Everywhere, what I see — which is maybe a bit different than how I think — is that done correctly, these tools are going to allow us to operate at the next level in everything we are doing. It’s not like you won’t do what you were doing before. You will start from a higher foundation. I wasn’t there when, I don’t know, spreadsheets rolled out to companies. I have to think back to how did people do all this financial analysis before? And I’m sure it changed over a period of three to four years fundamentally, and we got used to it.
I think agents and so on are a version of it. It’s not like you’re not going to plan birthday parties. Let’s say you’re planning a trip somewhere. Maybe you’re actually spending your time thinking about the actual things you want to do with your time versus chasing opening times and how to get tickets and so on. It elevates everything to a different foundation is how I think about it.
Let me ask you about that and agents. Some of those demos are fascinating. The idea that Search is going to build custom software for everybody seems like an idea in software engineering, a first impression. The idea is that you’re going to ask the computer a question, and the response will be for it to make you software that helps you get to an answer. I’m fascinated by this idea, but that is fundamentally changing Search.
And then you look at Gemini Spark, which is your agent platform in the cloud where you will say, “Go book me some tickets,” and Spark might run around and book you some tickets or do some task for you. And then there’s Antigravity, the agentic coding platform. Broadly, every year there’s a new paradigm for AI. There were LLMs first, and then maybe we’re going to change some LLMs together, then there’s reasoning, and then now we’re at agents. Is this the foundation, or is there another paradigm shift to come?
It’s a great question. We are laying most of the building blocks in place. Fundamentally being able to reason, use tools, and code is a lot like having intelligence and reasoning — being able to plan, being able to look up things, use tools, and, if you need as part of that, to build something. You are laying all the primitives. Antigravity is for developers, but the Antigravity engine, the harness, is built into Gemini now. And Spark is just a mode of Gemini. Over time, it’s a feature. We are positioning it, but it’s just a tab within Gemini.
So you’re bringing that agentic harness. Users don’t need to think about it. Developers will understand it. Over time, in Spark, they can code powerful things. But as users, you may be building something, creating something, planning a trip, and all that is working behind the scenes.
We are laying a lot of the primitives of what we need for agents to work end to end, and more importantly, for AI to work. This long-running vision of Google Assistant we’ve all had and worked through myriad forms of it and failed to fully do it well, we are closer than ever before to delivering on that promise. We haven’t delivered it yet, but that’s the journey which I think is now closer than ever before.
I look at all the products, and they do seem like they should converge. You have the new Intelligent Search box, and I definitely want to talk about Search in more detail. But you look at that search box and then you look at, say, Canvas which makes you the apps. You’re planning a wedding, and it’ll just make you an app to help you plan a trip or a wedding or something. And then you have Spark which can go off and do things. I looked at that and I was talking to people yesterday, and it just seems obvious that that should be one product.
It will. I gave the earlier Notebook example of like, you’re creating Notebooks… but what are Notebooks? You’re effectively putting all the context you want in one place and then working off it. It’s folders as they’ve always existed for people, and Notebook should be a consistent primitive across the Google products you use. I just view agents that way. It shouldn’t matter. When you’re at the earliest stage of innovation, you create the capability. Teams are experimenting with it, but for a user over time, if you fire off planning a trip, it should work across both places is how I would think about it. You’re right in that.
There’s something very important about Google Search — it is a source of truth for people for however many years or even decades now. Go Google it, and you’ll get an answer, and that that answer is the same for you and me generally has been a very important idea. It is, I think, a fixture in the culture. Maybe Google is the last company saying it will just tell you the truth, out of all the companies out there.
Okay, but now we’re going to infinitely personalize the search box, and we’re going to infinitely personalize the Search experience. We’re all going to get different answers to queries. We’re all going to maybe even look at different interfaces depending on what we’re asking, what our personal context is, how much data Google has.
Do you think about that profoundly? How much can you destabilize the last common source of truth most people experience on the internet?
Look, there are factors well beyond our control, which is that people today have a wider variety of sources than ever before. People are getting content from so many different sources. But within the world of Google, I still think we deeply care about this being a source of knowledge and information. There are objective experiences and subjective experiences. What’s the capital of the USA? It’s not going to be custom-created for anyone. These are objective things. “Help me plan a nice trip to Montreal for a weekend” — naturally, the answers don’t need to be the same for everyone. There is a continuum there.
We deeply care about it. For certain categories of information, we do still anchor around authoritative information to present as much of an objective view as possible. And if it is health-related queries, we naturally tend to show more authoritative answers than if you’re saying, “What’s better? Should I go buy?”
Can I show you a search result?
Yeah.
A few years ago, I showed you a search result. I’ve been tracking this one for years.
I always love it. Amongst the 10 trillion queries…
Yes. Well, this one’s a favorite.
We have a very scientific, statistical way of doing this.
I think this is important, and I want to get into how consumers might be experiencing these products. So this is a search I just do all the time: “best Chromebook.” I’ll just show it to you. There it is.
So it starts with an AI overview. It just very confidently tells you the answer, and then there’s a bunch of sponsored boxes. And then the one that gets me is right below that, I believe the result is Reddit, and it has a top result in Reddit. It’s actually a different answer than the AI overview. And then there’s The New York Times, which has a different answer.
You scroll this and you’re like, “The AI overview is telling me one thing, the first organic result is fairly down the page, and all of these are different answers.” I hear what you’re saying about objective results and subjective results. “What laptop should I buy,” is somewhere in the middle of those things. I’m just curious how you think that experience for consumers is today in AI Mode and where you think it should go.
Look, to be very clear, in the world of AIO, we use an AI mode. We are organizing and giving context, but there are sources throughout, so you’re still presenting organic content in a different way. There are links and sources you’re given, but there is an opinion to go with it too, which is what you’re talking about.
Some of this will be iterative with users. One of the great things we find with search is it’s easy to measure user satisfaction. Over 25 years we’ve learned to measure user happiness, user satisfaction in a correlated way with improving the quality of the product, not for short term. That’s why we do these long-term studies. If we get any experience wrong, it shows in the metrics and we course-correct. We pride ourselves on the ability to track this over the long term — be it engagement, sessions, returning to a topic, the number of bounce-backs they do. It’s a very, very sophisticated way of looking at it. In some areas like that, the experience will continue to evolve.
Do you think that experience is good today?
It’s probably more opinionated than it should be for the particular query you showed me. That was my reaction as a user. That’s the scope for improvement is how I would say it, in a fast-evolving space, but I would expect that to happen in the product. My intuition there is, “Oh, that’s way more opinionated.” There is some chance that’s personalized to you. You may be testing it in a way that you’re uniquely personalizing. The reason that query might not be exactly representative, though, is that I know how you review all these things. There is some chance you’re in the .0001 percentile–
This is kind of why I’m asking about infinitely personalizable results, right? And I’m also asking if the experience is good, because I would bet that most people experience AI in Google Search all the time. They have that experience where they’re kicked to AI mode. There’s the stuff you can measure about user satisfaction, and then there’s how the public feels about AI.
I think there’s a pretty yawning gap between, “There’s these user numbers going up, and we’re close to a billion users, and the free products people are experiencing, how good they might be,” and then just the polling data. Young people dislike AI. It’s as objective as that gets. You can go ask them, and they will tell you in measurable ways they dislike it.
Eric Schmidt, the former CEO of Google, was booed at a college graduation speech he was giving. Seven in 10 Americans oppose data center construction. There’s some gap between the product experiences people are having and how they feel about the technology. Do you think you can close that gap? Do you think these products are good enough?
It is a very profound topic, and you’re linking the two things. AI is the most profound technology humanity’s going to deal with. It’s happening at a very fast pace. I don’t think humans are evolved for processing this much change, and the rate of change particularly over the last few years is incredibly high. And particularly with all that they’re hearing, people are trying to understand the future and in the personal context of their lives, including what it means at an economic level and so on.
It really makes sense why there is anxiety around this technology, and we should be very attuned to that. That’s an important topic, and that’s much broader and bigger than the facets of what’s happening. People don’t directly associate these two all the time. In some cases, yes, they are linked in certain ways.
People experience the free versions of these models in various products. They open their social media feeds and they see slop. They see headlines about all that stuff. They have the tools just presented to them. The Gemini sparkle shows up in all the Google products, whether you ask for it or not. And then I do think you link it to, “They’re asking for a lot of electricity, and maybe my rates will go up. And maybe all the jobs will go away,” and that’s pretty scary, and I don’t know if the value exchange is there.
These are good things to study. You’re being too specific on what’s happening versus I’m just broadening it out and saying that might be part of the explanation. I do think there are other cheaper factors too.
Do you think it’s just a marketing problem? I’ve heard your peers say that AI just has a marketing problem.
No, I don’t think so. That’s the point I’m making. I’m in fact arguing against it. I think it makes sense to me why people would feel concerns about it. It feels natural to me. People are standing and talking about how AI could make a lot of jobs go away. Why wouldn’t you feel a sense of anxiety about it? I think those are deeper issues which we have to tackle as a society. Yes, there’s concern about AI slop at a product level. All that is true. All I’m pointing out is it’s a multilayered problem. But I don’t think all the source of the data center angst is directly related to one specific experience you’re having in a product or something alone like that. That’s all the point I’m making, right? It is broader and bigger than that.
There’s a lot of AI slop out there. I feel it. In an early phase of technology with the competitive dynamic that exists, a lot of things are getting rolled out. But we also see empirically how people are using these products in very deep ways. If you go to a place where Waymo hasn’t come and you’ve just polled people, talking about self-driving cars, what you get in the polls is different from how they feel when they use these cars. Technology also goes through these things. People have pretty negative views of the internet too, by the way, if you ask about the internet. But it’s a fabric of our lives, and we have to adapt to it. All of that is simultaneously happening.
It’s a complex topic. To me, it feels like people are worried about rising energy prices, and if so, they want to make sure AI is not exacerbating the problem, and that’s a valid concern. And it’s up to us as an industry to make sure that if you’re building data centers, what can we do to make sure we aren’t contributing to that problem? I view it as our responsibility, not just us. And the government, there are bipartisan concerns around some of this stuff. For example, there’s a rate payer pledge we all signed up to with a set of commitments. Maybe there needs to be more done. All of that goes hand in hand. It’s important to talk about topics like skilling, workforce adaptations. We are driving a lot of change very fast through society. Those end up being very important topics as well.
There are concerns at all those levels, and I expect those concerns to be meaningful as we go forward. Many years ago I said, “This is more profound than fire or electricity,” and so we have always felt that. Or think about deep-fakes and how do you know whether something is real? These models are getting better at simulating reality. This is why we’re working so hard. We are open-sourcing it, we are pulling many, many partners together, and it’s great for me to see the industry collaborate on a topic like this. Cybersecurity is another good example. These are all real concerns.
As an industry we need to do more. Governments will have a stronger role to play, and the public needs to be involved. You cannot have the most consequential technology rolling out the world in a way in democracies without public citizens rightfully having a voice around it. It is really important that we go through this phase, and that’s how we learn how to adapt.
My argument is that the products do the marketing work. That’s my push. I’m still waiting to see the killer app for consumers that does it. I think we have the killer app for enterprise.
One point, there are times I’ve gone through a health journey in Gemini. It feels more than like a killer app to me, better than anything I’ve ever done before. People are going through those experiences too.
I want to talk about the web, the health journey in Gemini that requires a rich data set of health information on the web to exist. You’re training Gemini on YouTube videos, right? Veo requires the YouTube ecosystem to operate and to be fruitful, to make new work in. You and I have discussed the concept I call Google Zero for many years, the idea that you will stop sending traffic to the web. You’ve disagreed with me that this is real.
Very much so. It hasn’t happened in the last many years.
Well, I’m just going to read you a quote. This time it’s not me, and I didn’t feed this to him. Roger Lynch, the CEO of Condé Nast, did an interview with TBPN last week and he said: “Every year our search traffic was down more than we had forecast, so last year I told our teams, ‘Assume there is no search. You have to have your businesses planned as if search is zero.'”
That is Google Zero. Condé Nast is saying, “We’re assuming that search will go to zero.” How would you respond to that, the idea that one of the biggest, most iconic publishers in the world is saying, “I can’t depend on this anymore”?
Look, first of all, the information ecosystem is so much broader beyond Google, by far. We see it in the data, you see it everywhere. So if any publisher over the last 10 years… I would look at The Verge and I would say where you were when you first took over, how much it’s evolved since then, the types of content you make, where all you put that content out, how all users are coming to you. It’s exceptionally dynamic, and so it makes sense to me every publisher is adapting to this new world.
We are adapting to the evolving world and how users are consuming technology. We had to do this when the world shifted from web to mobile. We are shifting it from a world of mobile to people having ongoing conversations, chatting with these products, talking to them, consuming it in voice and many different form factors.
People are expressing preferences for various types of content. They’re looking for user-generated content. They’re looking for podcasts. They’re looking for that. Through it all, we are very committed to both meeting user expectations, and also connecting them to what’s out on the web. Just even in the last year, even since we’ve launched these features, we’ve gone back and added more links. Another area where behavior is changing is that many publishers, rightfully so, are thinking about subscription models.
Sure. But I’m just saying Condé Nast is saying, “We’re going to assume our search traffic is zero, given the trends that we see.” Should they assume that?
Look, I always view… People understand their businesses better… I mean, I’m not in a position to tell such an iconic publisher what they should think about their business or plan. If they are building content that is high-quality and people like it, I expect us to reflect that in our products. That much I can commit to them.
But I think more than any other company through this evolution, we are working very hard to make sure people can get connected, and we are planning to do it in Search and Gemini, and that still underpins a lot of what we do. But there is evolution. As the technology improves, low-quality clicks get filtered out. That’s a natural evolution we see. We see it in our metrics. Bounce clicks are going down. And so those are all dynamics.
People are going to a wider array of information, and there are more people producing information than ever before. That pie is growing. All these dynamics are happening. It’s a complex ecosystem, but our commitment is to make sure we reflect the vastness and diversity of the content, and we do think people want to connect ultimately to these sources, but we are trying to meet them in those moments, and people come with very different intent and very different moments.
One of the small features we have done, but very important I think, is if you’ve subscribed to something, we reflect that as a preferred source for you as a user. But that’s a new change which we didn’t have before. We are adapting to the fact that publishers are increasingly turning to subscription offerings too.
Publishers and YouTube creators, should they be able to opt out of training to get surfaced in Search?
This is a much broader topic. Both laws and regulations will have to evolve. The courts will have to be in. It’s important to protect copyright. It’s important to protect fair use. And so these are constructs which will evolve dynamically through that.
But do you want to be in a bunch of lawsuits with YouTube creators? You’re in a lawsuit with publishers in the UK. That rhetoric in that lawsuit is getting increasingly heated. Google has said that the proposed solution is a “free rider charter.” Every year the News Media Association sends me a quote to read to you, and they say, “Google calling us free riders is obviously ridiculous. It’s basic supply chain economics. If the value were really all on Google’s side, they would simply allow publishers to opt out.”
Do you want to be in that same fight with a bunch of creators on YouTube about opting out?
Look, we are constantly — as part of Gemini developing…
We did offer a new opt-out with Google-Extended, and we are in conversations with publishers. We’ll take feedback and over time work through what makes sense. Obviously we are not the only player in a big ecosystem. We are also trying to put out products which are competitive to other products out there. All the publishers will also write an article saying the product is not very good. So it is more complicated than it looks.
You have spent more time thinking about the web and the health of the web and the necessity of the web. Paint me the picture for what a healthy web looks like in an agentic search world.
One of the arguments I’ve made over time and I actually see it playing around a little bit more, is I’ve started using the web more again over the last year to year and a half. All these AI experiences have brought the web back more. There was a time when it felt like… But I always felt the web would be vibrant. In fact, I’ve argued the web is going to be vibrant every year, and I would still argue it today. The web is constantly evolving. I’ve never seen anything as dynamic as the web, which is why it’s been such a privilege to be part of that evolution.
I look at agents, and that is the next evolution of the web, which we will deal with, and I think it will evolve the web pretty profoundly. There will be a lot of debates about what’s okay, what’s not, but people want to put out information, to connect with other people. People want to be connected. People aren’t trying to be in a siloed world, detached. That doesn’t reflect the reality of the human experience. I think the web is going to play as central a role on it as ever before. In fact, the Universal Commerce Protocol, if anything, what we announced yesterday, I think people are slightly underestimating the impact of it.
Actually, can I juxtapose that? There are a lot of muscular announcements about new products, new features, and agentic tools you can use, and UCP and Amazon and Walmart and everyone saying, “We’re going to use a new standard we’re building for shopping,” and all that is very tangible.
And then I/O ended with Demis Hassabis, the CEO of DeepMind, coming out, and he said this thing that I have not been able to stop thinking about. He said, “Google’s cutting-edge research and products will help unlock AGI’s incredible potential for the benefit of the entire world. When we look back at this time, I think we will realize that we were standing in the foothills of the singularity.”
Can you tell me what it means to be in “the foothills of the singularity”?
Demis and I have had long, deep conversations on this topic. In this context, the advent of AGI is what he thinks of as the singularity.
Do you have a definition of AGI? Have you debated it? Do you have an agreement?
We debate it a lot. I think both Demis and I are very close in how we think about things. There is a harder definition of AGI, which is that it has to be more comprehensively able to do a wide range of tasks, including cognitive tasks, in a way that’s comparable. We’ll at some point actually put it out as a company, and we are working on that. But that’s what he’s talking about in this context.
By the way, I think it’s important for us to understand that this technology is progressing very rapidly. Later today, I’ll be going and spending time with our AI researchers, not just in our company, but also amongst the frontier labs. There’s wide consensus that this technology, AGI, is… people may quibble around whether it will be three years, but the technology’s coming sooner rather than later. It’s more important to communicate that because — to an earlier part of the conversation — it’s important that we as a society understand it and are preparing as much as possible.
I asked you this question maybe the first time we ever talked about AI. I asked you if language was intelligence. And the progression here is we’re layering more and more on LLMs. We’re doing longer chains of reasoning, we’re building harnesses, we’re doing all this stuff, but the core technology is still transformers. It’s still the thing Google invented so long ago. Can LLMs get you to AGI? Is that path clear?
The trajectory over the last three years has been incredible. The LLMs of today have evolved in many ways too. We are constantly evolving it. To me, it’s like asking, can computers get us to the way—? The von Neumann architecture is still what powers most computers today, but he won’t recognize the modern one of our TPU pods. Or maybe he would. There’s still a lot of commonality to it. The underlying technology keeps evolving so profoundly. I look at every year we have had major breakthroughs. I mean, you just saw us demo in Antigravity an ability to prompt and create an operating system.
It’s very dangerous for Google to be able to make new operating systems.
We’ll have to make sure we don’t token max on creating… I’ll give you that. It’s fair, but that is the power of what these things are doing, right? There are the top mathematicians in the world, top physicists in this world who are interacting with these tools and using them in important ways, but can these tools fundamentally make novel scientific discoveries on their own? Not yet.
It’s remarkable how much it’s progressed. I do think it has important evolutions to happen, and then there are strong opinions out there in the world about how much of a real understanding of the world you need to take that next leap. I’m pretty optimistic that we will continue to make a lot of progress.
What is your timeline? Is it three years, or five years, to AGI? Where are you at?
I have always answered it this way: I think that timeline doesn’t matter because the rate of progress means you’re dealing with ever more intelligent systems in a profound way. So the way I would answer that question, three years from now, whether you and I call it AGI or not doesn’t matter because it’ll be very, very powerful, and we have to prepare for it.
Sundar, this was great. Thank you so much for taking the time yet again.
Yeah, thanks, Nilay. Pleasure.