英伟达黄仁勋最新发文:AI就是五层蛋糕,每一层都是万亿机会

比推Pubblicato 2026-03-11Pubblicato ultima volta 2026-03-11

Introduzione

英伟达黄仁勋发文提出,人工智能是像电力和互联网一样的基础设施,而非单一应用。他将AI比作一个五层蛋糕结构,从底层到顶层依次为:能源、芯片、基础设施、模型和应用。每一层都代表万亿级别的机会,且各层相互拉动、共同发展。 AI的核心突破在于能够实时生成智能,理解非结构化信息,并基于上下文进行响应,这彻底改变了传统预编程软件模式。能源层是基础,决定了智能生产的硬性上限;芯片层负责高效转化为计算;基础设施层包括AI工厂的建设和运营;模型层涵盖语言、生物、物理等多领域理解;应用层则创造实际经济价值,如药物研发、自动驾驶和工业机器人。 黄仁勋强调,全球正在经历史上最大规模的AI基础设施建设,需要大量技术工人参与,且AI将提升各行业生产力,创造增长机遇。目前AI模型已达到可大规模应用的门槛,开源模型进一步加速发展。未来,每个国家和公司都将参与AI建设,而当前仍处于早期阶段,基础设施、人才和机会尚有巨大发展空间。

原文标题:AI Is a Five‐Layer Cake

来源:Nvidia

编译:BitpushNews


人工智能是当今塑造世界最强大的力量之一。它不是某个聪明的应用程序或单一的模型;它是像电力和互联网一样的基础设施。

AI运行在真实的硬件、真实的能源和真实的经济学之上。它摄取原材料,并将其大规模转化为智能。每家公司都将使用它。每个国家都将建设它。

要理解AI为何以这种方式发展,从第一性原理出发,审视计算领域发生的根本性变化会有所帮助。

从预录软件到实时智能

在计算历史的大部分时间里,软件都是预先录制好的。人类描述一种算法。计算机执行它。数据必须被仔细地结构化,存储到表格中,并通过精确的查询来检索。SQL之所以变得不可或缺,是因为它让那个世界变得可行。

AI打破了这种模式。

我们第一次拥有了能够理解非结构化信息的计算机。它可以看图像、读文本、听声音并理解含义。它可以推理上下文和意图。最重要的是,它能实时生成智能。

每一个回应都是新创建的。每一个答案都取决于你提供的上下文。这不是软件在检索存储的指令。这是软件在按需推理和生成智能。

因为智能是实时产生的,其下方的整个计算堆栈都必须被重新发明。

AI作为基础设施

当你从工业角度审视AI时,它可以分解为一个五层堆栈。

能源

最底层是能源。实时生成的智能需要实时产生的能量。每一个生成的token都是电子移动、热量被管理、能量被转化为计算的结果。这之下再没有抽象层。能源是AI基础设施的第一性原理,也是系统能生产多少智能的硬性约束。

芯片

能源之上是芯片。这些处理器旨在大规模地将能量高效地转化为计算。AI工作负载需要巨大的并行性、高带宽内存和快速互连。芯片层的进步决定了AI能多快扩展以及智能能变得多便宜。

基础设施

芯片之上是基础设施。这包括土地、电力输送、冷却、建筑、网络,以及将数万个处理器编排成一台机器的系统。这些系统是AI工厂。它们不是为了存储信息而设计的。它们是为了制造智能而设计的。

模型

基础设施之上是模型。AI模型理解多种信息:语言、生物学、化学、物理学、金融学、医学以及物理世界本身。语言模型只是其中一类。一些最具变革性的工作正在蛋白质AI、化学AI、物理模拟、机器人和自主系统中进行。

应用

最顶层是应用,经济价值在这里被创造出来。药物发现平台。工业机器人。法律助手。自动驾驶汽车。一辆自动驾驶汽车是一个体现在机器中的AI应用。一个类人机器人是一个体现在躯体中的AI应用。同样的堆栈。不同的结果。

这就是五层蛋糕:

能源 → 芯片 → 基础设施 → 模型 → 应用。

每一个成功的应用都会拉动其下的每一层,一直向下延伸到维持其生命的发电厂。

我们才刚刚开始这个建设。我们才刚刚投入了几千亿美元。还需要建设数万亿美元的基础设施。

在全球范围内,我们正看到芯片工厂、计算机组装厂和AI工厂以前所未有的规模被建造。这正成为人类历史上最大规模的基础设施建设。

支持这一建设所需的劳动力是巨大的。AI工厂需要电工、水管工、管道装配工、钢铁工人、网络技术员、安装工和操作员。

这些都是需要技能、薪酬优厚的工作,而且目前供不应求。你不需要计算机科学博士学位就能参与这场变革。

与此同时,AI正在推动整个知识经济的生产力。以放射学为例。AI现在协助阅读扫描图像,但对放射科医生的需求仍在增长。这不是一个悖论。

放射科医生的目的是照顾病人。阅读扫描图像只是其中的一项任务。当AI承担了更多的常规工作时,放射科医生可以专注于判断、沟通和护理。医院变得更有效率。他们服务更多病人。他们雇佣更多员工。

生产力创造容量。容量创造增长。

过去一年发生了什么变化?

在过去的一年里,AI跨过了一个重要的门槛。模型变得足够好,可以大规模使用了。推理能力提高了。幻觉减少了。基础性(Grounding)显著改善。第一次,基于AI构建的应用开始产生真正的经济价值。

药物发现、物流、客户服务、软件开发和制造业中的应用已经显示出强大的产品市场契合度。这些应用强烈地拉动其下的每一层。

开源模型在这里扮演着关键角色。世界上大多数模型都是免费的。研究人员、初创公司、企业和整个国家都依赖开放模型来参与先进AI的发展。当开放模型达到前沿水平时,它们不仅仅改变了软件。它们激活了整个堆栈的需求。

DeepSeek-R1就是一个有力的例子。通过让一个强大的推理模型广泛可用,它加速了应用层的采用,并增加了对其下训练、基础设施、芯片和能源的需求。

这意味着什么

当你将AI视为关键基础设施时,其含义就变得清晰了。

AI始于一个transformer大语言模型。但它远不止于此。这是一场工业变革,重塑了能源的生产和消费方式、工厂的建设方式、工作的组织方式以及经济的增长方式。

AI工厂正在建设,因为智能现在是实时生成的。芯片正在被重新设计,因为效率决定了智能能多快扩展。能源变得核心,因为它设定了究竟能生产多少智能的上限。应用正在加速,因为它们底层的模型已经跨过了终于能够大规模有用的门槛。

每一层都强化着其他层。

这就是为什么建设规模如此之大。这就是为什么它同时触及如此多的行业。这也是为什么它不会局限于单一国家或单一领域。每家公司都将使用AI。每个国家都将建设它。

我们仍处于早期阶段。大部分基础设施尚不存在。大部分劳动力尚未得到培训。大部分机遇尚未被实现。

但方向是明确的。

AI正成为现代世界的基础设施。而我们现在做出的选择,我们建设得有多快,我们参与得有多广,以及我们部署得有多负责任,将塑造这个时代的面貌。

原文链接:https://www.bitpush.news/articles/7618907

Crypto di tendenza

Domande pertinenti

Q黄仁勋将AI比作五层蛋糕,这五层分别是什么?

A黄仁勋将AI比作五层蛋糕,这五层从底层到顶层依次是:能源、芯片、基础设施、模型、应用。

Q为什么说AI是像电力和互联网一样的基础设施?

A因为AI不是某个单一的应用程序或模型,而是运行在真实硬件、能源和经济基础上的基础设施,能够大规模将原材料转化为智能,每家公司和国家都将使用和建设它。

QAI如何改变了传统软件的工作模式?

A传统软件是预先录制的,执行固定算法,而AI能够理解非结构化信息,实时生成智能,根据上下文推理和生成回应,打破了预先录制和结构化数据的模式。

QAI的发展对劳动力市场有什么影响?

AAI创造了大量需要技能、薪酬优厚的工作,如电工、水管工、网络技术员等,同时通过提高生产力(如放射科医生专注于判断和护理)创造容量和增长,增加就业机会。

Q过去一年AI发展的重要变化是什么?

A过去一年AI模型变得足够好,可以大规模使用,推理能力提高,幻觉减少,基础性改善,基于AI的应用开始产生真正经济价值,开源模型如DeepSeek-R1加速了采用和需求。

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