为何英伟达的芯片能主导AI市场？

经济学人：

No other firm has benefited from the boom in artificial intelligence (ai) as much as Nvidia. Since January 2023 the chipmaker’s share price has surged by almost 450%. With the total value of its shares approaching $2trn, Nvidia is now America’s third-most valuable firm, behind Microsoft and Apple. Its revenues for the most recent quarter were $22bn, up from $6bn in the same period last year. Most analysts expect that Nvidia, which controls more than 95% of the market for specialist ai chips, will continue to grow at a blistering pace for the foreseeable future. What makes its chips so special?

没有其他公司像英伟达一样从人工智能 (ai) 的繁荣中受益。自 2023 年 1 月以来，这家芯片制造商的股价已飙升近 450%。 Nvidia 的股票总价值接近 2 万美元，目前是美国第三大市值公司，仅次于微软和苹果。最近一个季度的收入为 220 亿美元，高于去年同期的 60 亿美元。大多数分析师预计，控制着 95% 以上专业人工智能芯片市场的英伟达将在可预见的未来继续以惊人的速度增长。是什么让它的芯片如此特别？

Nvidia’s ai chips, also known as graphics processor units (gpus) or “accelerators”, were initially designed for video games. They use parallel processing, breaking each computation into smaller chunks, then distributing them among multiple “cores”—the brains of the processor—in the chip. This means that a gpu can run calculations far faster than it would if it completed tasks sequentially. This approach is ideal for gaming: lifelike graphics require countless pixels to be rendered simultaneously on the screen. Nvidia’s high-performance chips now account for four-fifths of gaming gpus.

Nvidia 的人工智能芯片也称为图形处理器单元 (GPU) 或“加速器”，最初是为视频游戏设计的。他们使用并行处理，将每个计算分解为更小的块，然后将它们分配给芯片中的多个“核心”（处理器的大脑）。这意味着 GPU 运行计算的速度比按顺序完成任务时快得多。这种方法非常适合游戏：逼真的图形需要在屏幕上同时渲染无数像素。 Nvidia 的高性能芯片目前占游戏 GPU 的五分之四。

Happily for Nvidia, its chips have found much wider uses: cryptocurrency mining, self-driving cars and, most important, training of ai models. Machine-learning algorithms, which underpin ai, use a branch of deep learning called artificial neural networks. In these networks computers extract rules and patterns from massive datasets. Training a network involves large-scale computations—but because the tasks can be broken into smaller chunks, parallel processing is an ideal way to speed things up. A high-performance gpu can have more than a thousand cores, so it can handle thousands of calculations at the same time.

令英伟达感到高兴的是，它的芯片有了更广泛的用途：加密货币挖矿、自动驾驶汽车，以及最重要的人工智能模型训练。支撑人工智能的机器学习算法使用了深度学习的一个分支，即人工神经网络。在这些网络中，计算机从大量数据集中提取规则和模式。训练网络涉及大规模计算，但由于任务可以分解为更小的块，因此并行处理是加快速度的理想方法。高性能GPU可以有一千多个核心，因此可以同时处理数千个计算。

Once Nvidia realised that its accelerators were highly efficient at training ai models, it focused on optimising them for that market. Its chips have kept pace with ever more complex ai models: in the decade to 2023 Nvidia increased the speed of its computations 1,000-fold.

一旦英伟达意识到其加速器在训练人工智能模型方面非常高效，它就专注于针对该市场对其进行优化。其芯片与日益复杂的人工智能模型保持同步：在截至 2023 年的十年中，Nvidia 将其计算速度提高了 1,000 倍。

But Nvidia’s soaring valuation is not just because of faster chips. Its competitive edge extends to two other areas. One is networking. As ai models continue to grow, the data centres running them need thousands of gpus lashed together to boost processing power (most computers use just a handful). Nvidia connects its gpus through a high-performance network based on products from Mellanox, a supplier of networking technology that it acquired in 2019 for $7bn. This allows it to optimise the performance of its network of chips in a way that competitors can’t match.

但英伟达估值飙升并不仅仅是因为更快的芯片。它的竞争优势延伸到另外两个领域。一是网络。随着人工智能模型的不断发展，运行它们的数据中心需要将数千个 GPU 捆绑在一起以提高处理能力（大多数计算机只使用少数几个）。 Nvidia 通过基于 Mellanox 产品的高性能网络连接其 GPU，Mellanox 是 Nvidia 于 2019 年以 70 亿美元收购的网络技术供应商。这使得它能够以竞争对手无法比拟的方式优化其芯片网络的性能。

Nvidia’s other strength is cuda, a software platform that allows customers to fine tune the performance of its processors. Nvidia has been investing in this software since the mid-2000s, and has long encouraged developers to use it to build and test AI applications. This has made cuda the de facto industry standard.

Nvidia 的另一个优势是 cuda，这是一个软件平台，允许客户微调其处理器的性能。 Nvidia 自 2000 年代中期以来一直在投资该软件，并长期以来鼓励开发人员使用它来构建和测试 AI 应用程序。这使得cuda成为事实上的行业标准。

Nvidia’s juicy profit margins and the rapid growth of the ai accelerator market—projected to reach $400bn per year by 2027—have attracted competitors. Amazon and Alphabet are crafting ai chips for their data centres. Other big chipmakers and startups also want a slice of Nvidia’s business. In December 2023 Advanced Micro Devices, another chipmaker, unveiled a chip that by some measures is roughly twice as powerful as Nvidia’s most advanced chip.

Nvidia 丰厚的利润率和人工智能加速器市场的快速增长（预计到 2027 年每年将达到 4000 亿美元）吸引了竞争对手。亚马逊和 Alphabet 正在为其数据中心打造人工智能芯片。其他大型芯片制造商和初创公司也想从英伟达的业务中分得一杯羹。 2023 年 12 月，另一家芯片制造商 Advanced Micro Devices 推出了一款芯片，从某些方面来看，其性能大约是 Nvidia 最先进芯片的两倍。

But even building better hardware may not be enough. Nvidia dominates ai chipmaking because it offers the best chips, the best networking kit and the best software. Any competitor hoping to displace the semiconductor behemoth will need to beat it in all three areas. That will be a tall order.■

但即使构建更好的硬件也可能还不够。英伟达在人工智能芯片制造领域占据主导地位，因为它提供最好的芯片、最好的网络套件和最好的软件。任何希望取代半导体巨头的竞争对手都需要在所有三个领域击败它。这将是一项艰巨的任务。