谷歌、微软激战AI PC:本地算力是智商税,云电脑才是终极形态?

marsbitPublished on 2026-05-15Last updated on 2026-05-15

Abstract

谷歌近日推出全新“安卓电脑”产品线,定位高端生产力,其核心思路是将云端AI深度集成,而非依赖本地硬件算力。这引发了关于AI PC未来发展方向的讨论:当前多数AI PC仍基于传统Windows架构,本地AI算力有限,主要任务实际依赖云端完成,导致硬件AI溢价的价值存疑。 文章指出,云电脑模式可能更适合AI PC。与对延迟极度敏感的云游戏不同,AI任务对网络延迟容忍度较高,瓶颈在于算力而非网速。谷歌的安卓电脑将AI融入系统各处,实现随时随地的智能交互,且硬件上兼容X86和ARM架构,凸显云端为核心的理念。阿里云等厂商也推出了集成大模型能力的AI云电脑服务。 面对AI化趋势,产业链各方反应不同:芯片厂商(如英特尔、AMD)既强调终端算力,也积极争夺云端数据中心订单;终端厂商多在传统架构上添加AI功能,手机品牌则致力于跨设备AI生态;苹果凭借软硬件一体化和产品下沉策略寻求突破;微软则通过定义硬件标准、系统底层集成Copilot等方式,结合云端与端侧能力。 安卓电脑代表了一种“轻本地、重云端”的新思路。在存储成本高企、消费级本地算力遭遇瓶颈的背景下,这种方案更具想象力和成本优势。未来的PC形态竞争,将是云端能力、系统重构与生态整合的全面较量。AI正在重新定义PC,未来或许只需基础硬件和网络连接,即可通过云端释放强大生产力。

赶在Google I/O大会前,谷歌于5月13日凌晨召开了Android 17的预热会。出乎意料的是,这场活动上谷歌毫无征兆地公布了全新产品系列——安卓电脑。不同于Chromebook,安卓电脑的定位偏高端,并且把生产力作为了核心卖点。谷歌已经不满足于入门市场,要在上网本之外的PC领域抢占更多的地盘。

AI PC的概念最近几年很火,无数PC芯片和终端厂商都在强调自家产品的AI特性,不厌其烦地一遍又一遍鼓吹AI给PC使用场景带来的新变化。而安卓电脑的横空出世,则向外界展示了AI PC的全新方案:不再依赖于传统的桌面端系统,云端AI不是附属而是核心,由此衍生出一切相关功能。

(图源:谷歌)

如果安卓电脑能够成功,那么云电脑很有可能会成为AI时代的版本答案。

当下的AI PC,还不够「AI」

目前PC行业内的AI PC,更像是给传统PC加上了一层AI的壳。芯片方面,英特尔和AMD都给PC处理器增加了独立的AI计算单元,以增强其在端侧AI方面的能力。系统和生态方面,终端厂商纷纷在系统中构建自己的AI应用,包括自家的电脑管家、智能体等,并且接入外部的大模型。

不过,这类AI PC本质上还是传统Windows电脑,AI更像是锦上添花的功能。而且,AI PC上实现的AI场景,绝大部分都是基于云端AI,包括文档总结修改、图片生成以及各种「龙虾」工具。

尽管芯片厂商一直宣传自家芯片的本地AI能力,还强调用CPU、GPU+NPU异构计算部署开源模型的场景。但现实中,消费级的PC芯片能提供的AI算力始终很有限,毕竟不是每个消费者都有一张5080的显卡、32GB起步的内存。

(图源:京东)

这种情况下,一台普通的消费级PC,很难真正运行大参数的本地模型,也就无法真正承担复杂一点的AI任务。

前阵子OpenClaw爆火,直接让Mac mini断货并涨价。但绝大部分人都是在用云端模型来「养虾」,各种龙虾部署教程都会提到哪家AI的Token便宜、怎么减少Token消耗。

(图源:Gitbook)

而这样一来,新的问题出现了:既然AI PC还是要依赖云端AI实现AI场景,那么AI PC本身的硬件价值是什么?

毕竟,理论上说,一台没有AI芯片溢价的传统PC,只要能联网接入云端AI,也能摇身一变成为一台AI PC。

甚至乎,我们能够更激进一点,大幅削减PC的硬件配置,只要能有屏幕、键盘和联网能力,就能成为云AI电脑。AI的快速发展和普及,似乎能让「云电脑」这个并不新鲜的物种,迎来一个爆发的机会。

云电脑+AI,才是AI PC的未来?

对我们来说,云电脑并不是一个陌生的东西。前几年爆火的云游戏,本质上就是以云电脑的形式实现的。彼时,5G全面普及,低延迟和大吞吐特性被视作普及云电脑的灵丹妙药。

但现实很骨感,云游戏这个概念始终不温不火。谷歌2019年推出的云游戏服务Stadia推出不到三年就匆匆下线,根据海外媒体的评测和用户反馈,Stadia如果要达到接近本地游戏平台的流畅体验,对网络质量要求极高,比如要用本地高速宽带进行有线联网,甚至用WiFi游玩体验都会大幅下降,遑论用5G这种波动更大的移动网络了。

(图源:谷歌)

不过,云游戏对网络延迟高度敏感,但在线AI的宽容度则高很多。作为普通用户,我们已经习惯了AI在回答问题和处理任务需要时间「思考」,对AI的结果反馈不会像游戏那样急切。

说到底,AI反应速度的瓶颈不在于网速,而在于算力。即便你安装一款本地大模型,它仍然需要足够的推理时间才能生成答案。

因此,我们认为,云电脑这种形式,天然就适合AI PC。而谷歌的安卓电脑,则在用一种有别于传统PC的模式来打造AI PC。在安卓电脑上,AI不是附属品,而是核心功能。谷歌表示,现在大部分AI工具都是独立的App,用户要把数据复制到AI界面里才能用上AI功能。而安卓电脑则把AI融合到系统的每一处,最直观的,鼠标指针移动到哪里,AI就在哪里出现,AI会捕捉指针附近的文本、图片、代码等信息,直接处理和操作。

(图源:谷歌)

另外,安卓电脑的实现方案,非常多元。对于安卓电脑,谷歌提供的更多是产品思路和实现形式,硬件本身还是需要合作厂商来搭建。按照谷歌公布的合作品牌,主要分为芯片和终端两大类,前者有英特尔、高通、联发科,后者有惠普、联想、宏碁、华硕、戴尔。

如果从芯片品牌来看,可以发现谷歌并不在乎安卓电脑用什么架构的芯片,X86也行、ARM也行。毕竟,目前来看,安卓PC上AI场景的实现,仍然高度依赖云端Gemini,本地硬件的算力则相对没有那么重要。

此外,互联网和云服务厂商们,一直在提供云电脑服务,并且在朝AI PC的方向进化。

以阿里来说,2024年就上线了无影AI云电脑,不仅有强悍的云端硬件配置,还给力大模型完善的支持。到了2026年,无影AI云电脑进一步升级,提供了对OpenClaw养虾的全面支持,能一键部署、直接接入千问,还能和钉钉、飞书、微信等通讯工具打通。

(图源:阿里云)

还有一点值得注意,AI巨头们在AI基础设施建设上疯狂军备竞赛,成为存储涨价的「元凶」。而且,短期内看不到存储降价的可能性。这样一来,消费级PC的配置升级会被进一步遏制,如果还用传统PC的迭代模式去打造AI PC,将会变得举步维艰。与其高成本堆算力天花板明显的本地AI配置,不如干脆把AI任务直接交给云端。

时代变了,PC厂商们要如何应对?

PC AI化已经是不可逆转的大趋势,整个PC产业链上的玩家,都在殚精竭虑地思考着如何登上AI PC的大船,它们扮演的角色不同、推进AI PC的形式也就不一样。

首先是芯片厂商,它们仍然在不断强调消费级芯片的AI算力,并且围绕它来构建AI场景。更重要的是,英特尔、AMD都在服务器市场上持续发力,不断争取AI巨头们的订单。

毕竟,AI厂商要进行AI基础设施建设,自然少不了大批的AI芯片采购。而能承接这些订单的,除了英伟达,剩下的主要就是英特尔、AMD这些传统CPU品牌了。

AMD的最新财报就显示,第一财季「数据中心」业务版块贡献的营收就达到了58亿美元,占比超过了一半。而且,英特尔、AMD的产能都满足不了订单量,AMD已经在台积电之外寻求三星等其他晶圆代工厂的协助。

(图源:AMD)

其次是终端厂商,这其中既包括联想、华硕、惠普等传统PC品牌,也有华为、小米、荣耀等新兴品牌。目前来看,它们对AI PC的打造主要还是基于英特尔/AMD芯片+Windows系统这套传统架构的基础上进行的,通过植入电脑管家、智能体等软件形式来增强PC的AI能力。

同时,手机品牌在AI PC领域还有一项优势,就是可以将PC产品和自家硬件生态中的手机、车机、穿戴、家居等各类不同形态的设备打通,AI能力能够跨设备无缝流转。以小米为例,超级小爱这个集智能体、AI助理、语音助手等多重能力于一身的工具,就能出现在小米生态里的各类设备上。

(图源:小米)

另外,苹果是AI PC领域中比较特殊的存在。Apple Intelligence公布的时间很早,但落地进程很拉垮,这就导致Mac的AI化很尴尬。而苹果在PC领域的优势仍然是独一档的软硬件一体化能力,对M系芯片和macOS系统有着绝对的掌控力。

最近,苹果将MacBook Neo的产量从500万增加到1000万台,并且不惜高价维持A18 Pro芯片的生产。由于这款笔记本的成功,在洛图公布的Q1线上笔记本市场数据中,苹果已经成为国内市场份额仅次于联想的PC品牌。

(图源:洛图)

在存储价格暴涨的大背景下,廉价款MacBook呈现出了惊人的吸引力。坦率说,MacBook Neo一开始并不被看好,更像是用来消耗A18 Pro库存的产物。这反映出,苹果是有能力做出成功的廉价PC的。一旦拥有扎实的用户基础,Apple Intelligence加持的MacBook就有希望在AI PC时代后来者居上。

最后,作为PC系统主导者的微软不能被忽略。微软对于AI PC的动作主要有三个方面,即AI PC硬件标准定义、系统重构和硬件架构多元化。

微软要求AI PC必须有40TOPS以上的算力和16GB以上的内存,在Windows底层引入了Windows Copilot Runtime,集成了多个小模型。同时,Windows提供了实时字幕、回顾(recall)等AI功能。

(图源:微软)

其中还有很关键的一点,Copilot用到了GPT的大模型技术和必应的联网能力,并且深度整合进了Windows系统、Edge浏览器和Office 365中,充分发挥自己的生态优势。而这,主要借助的仍然是云端AI能力。

写在最后

安卓电脑的出现,向固化多年的传统PC形态发起了挑战。它代表了AI时代PC发展的另一种产品思路:轻本地,重云端。

在存储成本居高不下、本地消费级算力遭遇瓶颈的今天,这种破除硬件壁垒、将核心生产力直接交由云端大模型接管的方案,无疑更有想象力。

当然,这场由AI引发的PC形态变革才刚开始。微软与传统PC厂商不会坐以待毙,他们仍然在强调端侧算力的重要性,但已经在全面引入云端AI;而苹果也会凭借软硬一体的生态优势和下沉策略继续抢蛋糕。接下来的PC市场,不再是单纯的硬件参数内卷,而是云端借力、系统底层AI重构和跨端生态的全面较量。

安卓电脑能否成为最终的版本答案,仍需经受住网络稳定性、数据隐私、用户习惯迁移等考验。但可以肯定的是,AI已经彻底重塑了PC的定义。

未来的PC,可能真的不再需要一张昂贵的显卡和大容量的内存,只需一块屏幕和通向云端的网络,就能释放出生产力。属于AI云电脑的全新时代,正在向我们走来。

本文来自“雷科技”

Related Questions

Q文章中提到目前AI PC的主要AI场景实现方式是什么?

A目前AI PC的主要AI场景绝大部分是基于云端AI实现的,包括文档总结修改、图片生成以及各种‘龙虾’工具。尽管芯片厂商强调本地AI算力,但消费级PC的本地硬件算力有限,难以运行复杂的大参数模型。

Q谷歌新推出的‘安卓电脑’在AI实现方案上与传统的AI PC有何不同?

A谷歌推出的‘安卓电脑’将云端AI作为核心而非附属。它不依赖于传统的桌面端系统,其AI功能被深度融合到系统的每一处(如鼠标指针指向哪里,AI就在哪里出现并直接处理信息)。它更强调‘轻本地、重云端’,硬件架构选择(X86或ARM)相对灵活。

Q为什么文章认为云电脑模式可能比传统AI PC更适合AI应用?

A文章认为云电脑模式可能更适合AI应用的主要原因有两点:一是AI任务对网络延迟的敏感度远低于云游戏,用户能容忍AI的‘思考’时间;二是当前存储成本高涨、消费级本地算力遭遇瓶颈,将核心AI计算任务交给云端更具成本效益和可扩展性。

Q微软在AI PC领域的布局主要包括哪三个方面?

A微软在AI PC领域的布局主要包括三个方面:一是定义AI PC硬件标准(如要求40TOPS以上算力和16GB以上内存);二是进行系统重构,在Windows底层引入Windows Copilot Runtime并集成AI功能;三是推动硬件架构多元化,并深度整合云端Copilot(基于GPT和必应)到其生态系统中。

Q文章指出在AI PC趋势下,苹果公司的潜在优势是什么?

A苹果在AI PC趋势下的潜在优势是其独一档的软硬件一体化能力和对M系芯片、macOS系统的绝对掌控力。此外,通过推出像MacBook Neo这样的成功廉价机型来扩大用户基础,可以为未来搭载Apple Intelligence的Mac产品在AI PC时代竞争奠定优势。

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marsbitYesterday 08:06

Gate Research Institute: The 'Wall Street-ization' Wave of Crypto Financial Products – Competition or Integration?

The article titled "Gate Research Institute: Are Crypto Financial Products Sparking a 'Wall Street' Wave—Competition or Convergence?" explores the evolving relationship between the crypto ecosystem and traditional finance (TradFi). The piece begins by reflecting on Bitcoin's original 2009 vision of decentralization, disintermediation, and moving away from banks. It then contrasts this with the 2024 landscape, where key crypto assets like Bitcoin are increasingly held through Wall Street products like ETFs issued by giants like BlackRock. The article questions whether this signifies that TradFi is systematically taking over the rights to issue, price, custody, and distribute crypto financial assets. The core argument is that this is not a zero-sum takeover but rather a bidirectional convergence where each side addresses the other's weaknesses. Crypto offers 24/7 global markets, programmable settlement, and open access but lacks compliant channels, institutional-grade custody, deep fiat liquidity, and mainstream distribution. TradFi possesses these but is constrained by legacy systems, limited operating hours, and slow settlement. Two primary convergence paths are highlighted: * **Path A (CEX to TradFi):** Exemplified by Gate, which has progressed from offering tokenized stocks and CFDs to providing direct, real stock trading (US, Hong Kong, South Korea) within its platform, using USDT. * **Path B (TradFi to Crypto):** Exemplified by Robinhood, which has integrated crypto trading, acquired exchanges like Bitstamp, and is moving traditional assets like stocks onto the blockchain via tokenization and its own Layer 2. Both paths are ultimately competing to become the next-generation, unified financial account—a "super account" where users can seamlessly trade cryptocurrencies, stocks, ETFs, RWA (Real World Assets), and tokenized treasury products in one interface. The growth of RWA and tokenized treasuries (e.g., BlackRock's BUIDL) is presented as the asset-layer fusion, providing stable, yield-bearing assets on-chain and acting as a bridge between the two worlds. In conclusion, the "Wall Street-ization" of crypto is framed as a mutual transformation. Decentralized ideals persist in the protocol layer, while at the application layer, a more efficient, global, and accessible unified capital market is emerging from this convergence. The future competition lies not between crypto exchanges and stockbrokers, but between platforms vying to offer the most comprehensive asset coverage, liquidity, and user experience within a single account.

marsbitYesterday 08:01

Gate Research Institute: The 'Wall Street-ization' Wave of Crypto Financial Products – Competition or Integration?

marsbitYesterday 08:01

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