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辉达黄仁勋描绘AI代理时代蓝图!AI PC今秋登场 一文看懂如何改变工作与生活

2026-09-14 09:20:58 网络 阅读(73)

辉达 (NVDA-US) 执行长黄仁勋近日发表重要演讲,宣告人工智慧(AI)已从生成式 AI 演进至全新形态「AI 代理」,并强调「实用 AI 时代」已正式开启。他从生产力释放、企业 IT 重构,到个人电脑全面革新,完整勾勒出这场科技变革的轮廓。

黄仁勋以全球最大程式码托管平台 GitHub 为例,具体说明 AI 代理带来的生产力爆发。

数据显示,GitHub 平台上的程式码提交次数从 2023 年的 3 亿次,成长至 2024 年的 4 亿次、2025 年的 5 亿次,而 2026 年前几个月,这个数字几乎暴增至三倍。

他指出,全球约有三千万名职业软体开发人员,每年创造逾一兆美元的薪资支出,却撑起全球规模高达 100 兆美元的产业。

然而,随着 AI 代理的介入,同样一兆美元的薪资投入,如今却能带来近三倍的产出,等同于释放了高达 9 兆美元的生产力。

面对外界对「AI 抢走工作」的担忧,黄仁勋态度直接且强硬:「有人说 AI 会减少工作岗位,这完全是无稽之谈。」

他强调,全球软体工程师的人数正持续增长,原因很简单,若工程师借助 AI 能创造如此惊人的产值,企业自然更愿意广纳人才。

Token 成为实用 AI 时代的核心货币

黄仁勋进一步指出,实用 AI 时代的降临,直接催生了对「Token」的海量需求。

Token 原本是 AI 领域的纯技术术语,如今已演变成 AI 产业衡量获利与营收的核心计量单位。各大 AI 企业无不竞相追求生成更多 Token、建设更多「AI 工厂」,而这也是台湾算力需求急遽攀升、相关硬体生态业者股价持续强劲的根本动因。

他更直言,未来职场的竞争维度将出现根本性转变:衡量个人产出的标准,将从过去的「工作量」(写了多少程式码、做了多少方案),转向「Token 效率」,即「你每天能透过 AI 生成多少 Token?」、「你的 Token 产出成本是多少?」

黄仁勋强调:「你不会被 AI 取代,但你可能会被那些精通使用 AI 的人替换。」

分析指出,这就像当年 Excel 普及的历史:会用 Excel 的人取代了只懂手写报表的人;未来,能熟练运用 AI 代理、产出更多 Token 的人,自然也将取代只靠手动作业的人。

AI 代理如何运作:理解、观察、推理、行动

在技术层面,黄仁勋详细阐述了 AI 代理的运作原理。

他表示,计算模式已发生根本性革命:过去是在作业系统中执行应用程式与程式码,而今天的新模式,是在「容器框架」中运行由一个或多个大型语言模型(LLM)构成的 AI 代理。

当接收到输入指令后,AI 代理将完成「理解→观察→推理→行动」的完整流程,并能调用试算表、网页浏览器、资料处理引擎等各类工具。

整个过程由软体统一编排,框架负责路由资讯、处理上下文、感知现状、进行推理并制定执行计划。

黄仁勋表示,这正是 AI 代理的核心运作逻辑。系统会像人类一样,同时管理短期与长期记忆,因此如何有效储存、检索与调度资讯,已成为 AI 代理架构中的关键能力。

在这套新架构下,大型语言模型(LLM)负责理解、推理与决策,而外层框架则扮演类似作业系统的角色,负责协调记忆体、工具以及各种功能模组,使整个系统能够顺畅运作。

黄仁勋指出,这代表 AI 发展的重要里程碑。随着新一代大型语言模型在推理、规划以及工具使用等能力上持续进步,再结合记忆体管理与工具编排机制,AI 已能完成过去难以实现的复杂任务。

传统电脑使用者必须开启应用程式,透过操作介面逐步完成工作;未来则只需向 AI 描述目标与需求,系统便能自行撰写程式、调用工具并产生最终成果。

黄仁勋认为,这将成为下一代电脑的主要运作模式,也是 AI 代理发展的终极方向。经过近两年的投入与开发,相关技术如今已从概念验证逐步走向实际应用。

企业 IT 面临全面重构:从管人到管代理

黄仁勋警告,AI 代理时代对企业 IT 架构构成前所未有的挑战。过去的企业 IT 系统以「人」为核心设计,着重让员工安全高效地使用工具;但未来企业内部运行的,不只是人,还有成百上千个自主运作的代理。

这些代理将存取公司核心财务数据与客户敏感资讯、执行程式码、对接外部系统,甚至代为发送电子邮件、签署合约,而现有的安全、权限与稽核体系,根本不足以因应这样的挑战。

他特别指出,AI 代理运作的时间尺度与人类截然不同:「AI 代理是没有耐性的,他们生活的世界不以秒计算,是以奈秒计算。」

正因如此,辉达在本次演讲中一口气发布了一整套代理基础设施,包括

  • Vera CPU(88 核心,专为代理设计)、
  • BlueField-4 STX(硬体层安全隔离)、
  • OpenShell(Agent 沙箱环境),
  • 以及 CUDA-X Agent Skills(代理调用 GPU 加速函式库的介面)。

他更直截了当地说:「每家公司内部都将有 AI 代理在运行,他们会意识到,AI 代理将需要自己的作业系统。」而那些以为完成资讯化建设就一劳永逸的企业,可能面临的是整套 IT 架构沦为「空架子」的风险。

黄仁勋举了一个具体例子:Cadence 的验证代理已经证明:晶片验证周期提升了 40 倍。不是快了一点,是快了一个数量级。

PC 迎来 40 年最大变革:从个人电脑到家庭 AI 超级电脑

在演讲中,黄仁勋也掀起了对个人电脑的革命性宣言。

辉达发布的 RTX Spark 晶片搭载 Blackwell GPU 与 20 核 Grace CPU、128GB 统一记忆体、FP4 算力达 1 Petaflop,可在本地端执行高达 1,200 亿参数的大型语言模型,采台积电 (2330-TW) 3 奈米制程,电晶体数量达 700 亿颗。

过去的 PC 是作业系统加应用程式的组合,使用者靠滑鼠键盘操控;而新一代 PC 则是在传统作业系统之上,叠加大型语言模型与代理执行阶段系统,使用者只需用自然语言与电脑对话,电脑便能跨档案、跨应用自主完成任务。

黄仁勋以智慧型手机的诞生作比:15 到 20 年前,电话是用来通话的工具;如今,你几乎用手机做所有事,唯一不用它做的,反而是打电话。

他说:「就像十年前我们重新定义了手机,从今天起,PC 的意义彻底变了。」

他更大胆预言,未来家庭中将出现「AI 超级电脑」:「就像现在许多家庭拥有家庭影院或洗碗机一样,总有一天你的家里会有一台 AI 超级电脑,它运行着你所有的代理和助手,一直为你处理各种事情。」

他形容,这台电脑最终将更像电影中的 R2-D2 或 C-3PO,而非一台传统意义上的个人电脑,就像家中的「数位管家」一样。

今年秋天,戴尔科技 (DELL-US) 、联想 (03396-HK) 、惠普 (HPQ-US) 、华硕 (2357-TW) 、微软 (MSFT-US) Surface 等品牌将推出逾 30 款相关笔记型电脑及 10 款桌上型电脑,Adobe(ADBE-US) 也已从头重构 Photoshop 与 Premiere,效能翻倍,而全球已有逾 100 家厂商投入适配。

总的来说,随着 AI 代理技术逐步成熟,科技产业人士认为,今年秋季上市的新一代 AI PC,可能将成为个人电脑发展史上的重要分水岭,其影响力甚至可与过去数十年的运算平台变革相提并论。

业界观察指出,市场讨论焦点不应仅停留在模型参数规模,而是电脑本身是否具备执行 AI 代理的能力。传统 PC 主要依赖使用者手动操作各类软体完成工作,而搭载新一代 AI 架构的电脑,则有望将许多流程交由 AI 自主处理,大幅改变人机互动模式。

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    "content": "<p>辉达 (<a data-symbol-template=\"USS:NVDA:STOCK:COMMON\" href=\"#\">NVDA-US</a>) 执行长黄仁勋近日发表重要演讲,宣告人工智慧(AI)已从生成式 AI 演进至全新形态「AI 代理」,并强调「实用 AI 时代」已正式开启。他从生产力释放、企业 IT 重构,到个人电脑全面革新,完整勾勒出这场科技变革的轮廓。</p>\n<p style=\"text-align:center;\"><img src=\"https://cimg.cnyes.cool/prod/news/6480760/l/557af8132ade628c86ce18d60fe1b7b0.jpg\" alt=\"\" style=\"width:50%;height:auto;border-radius:6px;margin:15px auto;display:block;\"></p>\n\n\n<p>黄仁勋以全球最大程式码托管平台 GitHub 为例,具体说明 AI 代理带来的生产力爆发。</p>\n\n<p>数据显示,GitHub 平台上的程式码提交次数从 2023 年的 3 亿次,成长至 2024 年的 4 亿次、2025 年的 5 亿次,而 2026 年前几个月,这个数字几乎暴增至三倍。</p>\n\n<p>他指出,全球约有三千万名职业软体开发人员,每年创造逾一兆美元的薪资支出,却撑起全球规模高达 100 兆美元的产业。</p>\n\n<p>然而,随着 AI 代理的介入,同样一兆美元的薪资投入,如今却能带来近三倍的产出,等同于释放了高达 9 兆美元的生产力。</p>\n\n<p>面对外界对「AI 抢走工作」的担忧,黄仁勋态度直接且强硬:「有人说 AI 会减少工作岗位,这完全是无稽之谈。」</p>\n\n<p>他强调,全球软体工程师的人数正持续增长,原因很简单,若工程师借助 AI 能创造如此惊人的产值,企业自然更愿意广纳人才。</p>\n\n<h6>Token 成为实用 AI 时代的核心货币</h6>\n\n<p>黄仁勋进一步指出,实用 AI 时代的降临,直接催生了对「Token」的海量需求。</p>\n\n<p>Token 原本是 AI 领域的纯技术术语,如今已演变成 AI 产业衡量获利与营收的核心计量单位。各大 AI 企业无不竞相追求生成更多 Token、建设更多「AI 工厂」,而这也是台湾算力需求急遽攀升、相关硬体生态业者股价持续强劲的根本动因。</p>\n\n<p>他更直言,未来职场的竞争维度将出现根本性转变:衡量个人产出的标准,将从过去的「工作量」(写了多少程式码、做了多少方案),转向「Token 效率」,即「你每天能透过 AI 生成多少 Token?」、「你的 Token 产出成本是多少?」</p>\n\n<p>黄仁勋强调:「你不会被 AI 取代,但你可能会被那些精通使用 AI 的人替换。」</p>\n\n<p>分析指出,这就像当年 Excel 普及的历史:会用 Excel 的人取代了只懂手写报表的人;未来,能熟练运用 AI 代理、产出更多 Token 的人,自然也将取代只靠手动作业的人。</p>\n\n<h6>AI 代理如何运作:理解、观察、推理、行动</h6>\n\n<p>在技术层面,黄仁勋详细阐述了 AI 代理的运作原理。</p>\n\n<p>他表示,计算模式已发生根本性革命:过去是在作业系统中执行应用程式与程式码,而今天的新模式,是在「容器框架」中运行由一个或多个大型语言模型(LLM)构成的 AI 代理。</p>\n\n<p>当接收到输入指令后,AI 代理将完成「理解&rarr;观察&rarr;推理&rarr;行动」的完整流程,并能调用试算表、网页浏览器、资料处理引擎等各类工具。</p>\n\n<p>整个过程由软体统一编排,框架负责路由资讯、处理上下文、感知现状、进行推理并制定执行计划。</p>\n\n<p>黄仁勋表示,这正是 AI 代理的核心运作逻辑。系统会像人类一样,同时管理短期与长期记忆,因此如何有效储存、检索与调度资讯,已成为 AI 代理架构中的关键能力。</p>\n\n<p>在这套新架构下,大型语言模型(LLM)负责理解、推理与决策,而外层框架则扮演类似作业系统的角色,负责协调记忆体、工具以及各种功能模组,使整个系统能够顺畅运作。</p>\n\n<p>黄仁勋指出,这代表 AI 发展的重要里程碑。随着新一代大型语言模型在推理、规划以及工具使用等能力上持续进步,再结合记忆体管理与工具编排机制,AI 已能完成过去难以实现的复杂任务。</p>\n\n<p>传统电脑使用者必须开启应用程式,透过操作介面逐步完成工作;未来则只需向 AI 描述目标与需求,系统便能自行撰写程式、调用工具并产生最终成果。</p>\n\n<p>黄仁勋认为,这将成为下一代电脑的主要运作模式,也是 AI 代理发展的终极方向。经过近两年的投入与开发,相关技术如今已从概念验证逐步走向实际应用。</p>\n\n<h6>企业 IT 面临全面重构:从管人到管代理</h6>\n\n<p>黄仁勋警告,AI 代理时代对企业 IT 架构构成前所未有的挑战。过去的企业 IT 系统以「人」为核心设计,着重让员工安全高效地使用工具;但未来企业内部运行的,不只是人,还有成百上千个自主运作的代理。</p>\n\n<p>这些代理将存取公司核心财务数据与客户敏感资讯、执行程式码、对接外部系统,甚至代为发送电子邮件、签署合约,而现有的安全、权限与稽核体系,根本不足以因应这样的挑战。</p>\n\n<p>他特别指出,AI 代理运作的时间尺度与人类截然不同:「AI 代理是没有耐性的,他们生活的世界不以秒计算,是以奈秒计算。」</p>\n\n<p>正因如此,辉达在本次演讲中一口气发布了一整套代理基础设施,包括</p>\n\n<ul>\n<li>Vera CPU(88 核心,专为代理设计)、</li>\n<li>BlueField-4 STX(硬体层安全隔离)、</li>\n<li>OpenShell(Agent 沙箱环境),</li>\n<li>以及 CUDA-X Agent Skills(代理调用 GPU 加速函式库的介面)。</li>\n</ul>\n\n<p>他更直截了当地说:「每家公司内部都将有 AI 代理在运行,他们会意识到,AI 代理将需要自己的作业系统。」而那些以为完成资讯化建设就一劳永逸的企业,可能面临的是整套 IT 架构沦为「空架子」的风险。</p>\n\n<p>黄仁勋举了一个具体例子:Cadence 的验证代理已经证明:晶片验证周期提升了 40 倍。不是快了一点,是快了一个数量级。</p>\n\n<h6>PC 迎来 40 年最大变革:从个人电脑到家庭 AI 超级电脑</h6>\n\n<p>在演讲中,黄仁勋也掀起了对个人电脑的革命性宣言。</p>\n\n<p>辉达发布的 RTX Spark 晶片搭载 Blackwell GPU 与 20 核 Grace CPU、128GB 统一记忆体、FP4 算力达 1 Petaflop,可在本地端执行高达 1,200 亿参数的大型语言模型,采台积电 (<a data-symbol-template=\"TWS:2330:STOCK:COMMON\" href=\"#\">2330-TW</a>) 3 奈米制程,电晶体数量达 700 亿颗。</p>\n\n<p>过去的 PC 是作业系统加应用程式的组合,使用者靠滑鼠键盘操控;而新一代 PC 则是在传统作业系统之上,叠加大型语言模型与代理执行阶段系统,使用者只需用自然语言与电脑对话,电脑便能跨档案、跨应用自主完成任务。</p>\n\n<p>黄仁勋以智慧型手机的诞生作比:15 到 20 年前,电话是用来通话的工具;如今,你几乎用手机做所有事,唯一不用它做的,反而是打电话。</p>\n\n<p>他说:「就像十年前我们重新定义了手机,从今天起,PC 的意义彻底变了。」</p>\n\n<p>他更大胆预言,未来家庭中将出现「AI 超级电脑」:「就像现在许多家庭拥有家庭影院或洗碗机一样,总有一天你的家里会有一台 AI 超级电脑,它运行着你所有的代理和助手,一直为你处理各种事情。」</p>\n\n<p>他形容,这台电脑最终将更像电影中的 R2-D2 或 C-3PO,而非一台传统意义上的个人电脑,就像家中的「数位管家」一样。</p>\n\n<p>今年秋天,戴尔科技 (<a data-symbol-template=\"USS:DELL:STOCK:COMMON\" href=\"#\">DELL-US</a>) 、联想 (<a data-symbol-template=\"HKS:03396:STOCK:COMMON\" href=\"#\">03396-HK</a>) 、惠普 (<a data-symbol-template=\"USS:HPQ:STOCK:COMMON\" href=\"#\">HPQ-US</a>) 、华硕 (<a data-symbol-template=\"TWS:2357:STOCK:COMMON\" href=\"#\">2357-TW</a>) 、微软 (<a data-symbol-template=\"USS:MSFT:STOCK:COMMON\" href=\"#\">MSFT-US</a>) Surface 等品牌将推出逾 30 款相关笔记型电脑及 10 款桌上型电脑,Adobe(<a data-symbol-template=\"USS:ADBE:STOCK:COMMON\" href=\"#\">ADBE-US</a>) 也已从头重构 Photoshop 与 Premiere,效能翻倍,而全球已有逾 100 家厂商投入适配。</p>\n\n<p>总的来说,随着 AI 代理技术逐步成熟,科技产业人士认为,今年秋季上市的新一代 AI PC,可能将成为个人电脑发展史上的重要分水岭,其影响力甚至可与过去数十年的运算平台变革相提并论。</p>\n\n<p>业界观察指出,市场讨论焦点不应仅停留在模型参数规模,而是电脑本身是否具备执行 AI 代理的能力。传统 PC 主要依赖使用者手动操作各类软体完成工作,而搭载新一代 AI 架构的电脑,则有望将许多流程交由 AI 自主处理,大幅改变人机互动模式。</p>\n<div class=\"related-articles seo-links\">\n  <h4>相关阅读</h4>\n  <ul>\n    <li><a href=\"/new/mg/article-9691.html\" title=\"「大卖空」贝瑞续看空:美股逼近重大高点 恐重演1987年股灾\">「大卖空」贝瑞续看空:美股逼近重大高点 恐重演1987年股灾</a></li>\n    <li><a href=\"/new/mg/article-4280.html\" title=\"升息、降息都不怕 华尔街齐看好「万全之策」:5年期美债最稳\">升息、降息都不怕 华尔街齐看好「万全之策」:5年期美债最稳</a></li>\n    <li><a href=\"/new/mg/article-1792.html\" title=\"避险大咖点名「三巨头」遭低估 市场狂追AI股宛如2000年泡沫\">避险大咖点名「三巨头」遭低估 市场狂追AI股宛如2000年泡沫</a></li>\n    <li><a href=\"/new/mg/article-4424.html\" title=\"苹果供应链机密外泄!iPhone 18 Pro资料流入暗网 台积电、高通也卷入\">苹果供应链机密外泄!iPhone 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    "createdAt": "2026-06-02T06:10:03.000Z",
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