<p>大约三十年前，互联网的出现改变了美国企业的一切。尽管互联网作为一项技术成熟需要许多年，企业也需要时间来意识到其全部潜力，但它积极地改变了商业的增长轨迹，并打开了以前不存在的新机遇。</p>
<p>自 1990 年代中期以来，华尔街一直在等待一种新技术或颠覆性创新，以复制互联网对商业的影响。人工智能（AI）似乎回应了这一呼唤。</p>
<p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy83OTc1MDIvYXJ0aWZpY2lhbC1pbnRlbGxpZ2VuY2UtYWktcm9ib3QtYmlnLWRhdGEtYnVsbC1tYXJrZXQtc3RvY2stY2hhcnQtZ2V0dHkuanBnJnc9NzAw?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy83OTc1MDIvYXJ0aWZpY2lhbC1pbnRlbGxpZ2VuY2UtYWktcm9ib3QtYmlnLWRhdGEtYnVsbC1tYXJrZXQtc3RvY2stY2hhcnQtZ2V0dHkuanBnJnc9NzAw"/></p>
<p>图片来源：Getty Images。</p>
<p>人工智能之所以成为如此引人注目的技术，是因为它的广泛实用性。基于人工智能的软件和系统有能力随着时间的推移变得更加智能和高效。此外，这些软件和系统可能能够在没有人类干预的情况下学习新任务。</p>
<p>对一些人来说，人工智能的潜力真的是无穷无尽。在《Sizing the Prize》中，普华永道的分析师预测，到 2030 年，人工智能将使全球国内生产总值增加 15.7 万亿美元，这些增长将来自生产力的提高和消费侧效应的结合。</p>
<p>一个 15.7 万亿美元的可寻址市场为多家公司提供了获胜的空间。但在过去两年中，半导体巨头 <strong>Nvidia</strong>（NVDA 0.34%）无疑是人工智能革命中最明显的受益者，其市值从 2022 年底的 3600 亿美元飙升至截至 11 月 11 日的 3.56 万亿美元。</p>
<h2>Nvidia 的运营扩展几乎无可挑剔</h2>
<p>投资者无需远行就能发现 Nvidia 为何成为华尔街最有价值的上市公司。其图形处理单元（GPU）已成为运营人工智能加速数据中心的企业的首选。Nvidia 的 H100 GPU，通常被称为 “Hopper”，以及其后继的 Blackwell GPU 架构，实际上是使人工智能软件和系统能够进行瞬时决策的 “大脑”。</p>
<p>根据 TechInsights 分析师的研究，Nvidia 在 2022 年向数据中心出货的 267 万 GPU 中占据了约 98% 的份额，以及在 2023 年出货的 385 万 GPU。预计今年它也不太可能失去其近乎垄断的市场份额，Hopper 芯片和 Blackwell 的订单已经积压。</p>
<p>此时提到，当对某种商品或服务的需求超过供应时，该商品或服务的价格往往会上涨。Nvidia 能够以 30,000 到 40,000 美元的价格出售 Hopper，这比竞争对手的人工智能 GPU 价格高出 100% 到 300%。鉴于 Nvidia 硬件所提供的计算优势，企业愿意支付这一溢价，这也转化为公司毛利率的显著提升。</p>
<p>公司的 CUDA 平台也应为其几乎无可挑剔的运营扩展而受到赞誉。CUDA 是开发者用来充分利用其 GPU 的软件工具包，包括构建大型语言模型（LLM）。它在保持 Nvidia 客户忠诚于公司解决方案生态系统方面发挥了关键作用。</p>
<p>最后，投资者被市场领先公司前所未见的增长率所吸引。当 2023 财年于 2023 年 1 月 29 日结束时，Nvidia 报告全年销售额为 270 亿美元。但根据华尔街对 2026 财年的预测，Nvidia 有望实现 1800 亿美元的收入。这是三年复合年销售增长率约为 88%！</p>
<p>然而，尽管其运营扩展几乎教科书般完美，但对 Nvidia 来说，有一个不可否认的威胁正在逼近——而几乎没有人谈论它。</p>
<p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy83OTc1MDIvYXJ0aWZpY2lhbC1pbnRlbGxpZ2VuY2UtYWktY2hpcC1udmlkaWEtZ3B1LWRhdGEtY2VudGVyLWdldHR5LmpwZyZ3PTcwMA?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy83OTc1MDIvYXJ0aWZpY2lhbC1pbnRlbGxpZ2VuY2UtYWktY2hpcC1udmlkaWEtZ3B1LWRhdGEtY2VudGVyLWdldHR5LmpwZyZ3PTcwMA"/></p>
<p>图片来源：Getty Images。</p>
<h2>这个威胁有可能将华尔街的人工智能宠儿拉下神坛</h2>
<p>正如大多数投资者可能已经意识到的，人工智能的惊人可寻址市场使企业争相分一杯羹。在接下来的几个季度中，Nvidia 将面临外部竞争的压力。</p>
<p>尽管 <strong>Advanced Micro Devices</strong>（AMD -0.33%）在 Nvidia 之后进入市场，但它在 MI300X 人工智能 GPU 的生产上没有遇到任何困难。AMD 最近还推出了其下一代芯片 MI325X，预计将在今年年底前投入生产。AMD 的芯片价格明显低于 Nvidia 的 Hopper 和 Blackwell，这可能使它们对希望在数据中心利用人工智能的企业具有吸引力。</p>
<p>然而，外部竞争并不是推翻 Nvidia 的最大威胁。相反，Nvidia 面临的最大直接阻力是内部竞争。</p>
<p>许多美国最具影响力的企业已经订购并在其高计算数据中心中使用 Nvidia 的 GPU。这包括 <strong>Microsoft</strong>（MSFT 0.40%）、<strong>Meta Platforms</strong>（META -0.49%）、<strong>Amazon</strong>（AMZN -1.22%）、<strong>Alphabet</strong>（GOOGL -1.85%）（GOOG -1.74%）、<strong>Tesla</strong>、OpenAI，以及将 Nvidia 的 GPU 集成到其可定制机架服务器中的人工智能基础设施巨头 <strong>Super Micro Computer</strong>。</p>
<p>截至 2024 年 7 月 28 日的三个月内，Nvidia 的四个客户——它并未披露其主要客户的名称——占其净销售额的 46%，第五个客户贡献不到 10%，但仍可能在高个位数范围内。我们可以自信地说，Nvidia 的一半收入来自仅五个客户。如果我必须猜测，我会认为这些客户是 Microsoft、Meta、Amazon、Alphabet 和 Super Micro（不按此顺序）。</p>
<p><img src="https://imageproxy.pbkrs.com/https://media.ycharts.com/charts/ef803252949883618de7b1017753a00c.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://media.ycharts.com/charts/ef803252949883618de7b1017753a00c.png"/></p>
<p>人工智能 GPU 的稀缺性使 Nvidia 的毛利率飙升。NVDA 毛利率（季度）数据来自 YCharts。</p>
<p>对英伟达的担忧在于，这些顶级客户大多数正在为各自的数据中心开发 AI-GPU。</p>
<ul>
<li>微软开发了 Azure Maia AI 芯片，可以用于训练大型语言模型并监督公司 Azure 云基础设施平台内的生成式 AI 解决方案。</li>
<li>Meta 正在内部开发 “Meta 训练与推理加速器” 芯片，以最大化其 AI 数据中心的潜力。</li>
<li>亚马逊正在开发多款 GPU 芯片，包括 Trainium2 和 Inferentia，旨在满足其全球领先的云基础设施服务平台 Amazon Web Services (AWS) 的客户需求。</li>
<li>Alphabet 依赖张量处理单元（TPU）来训练大型语言模型和进行推理。TPU 是为 AI 应用量身定制的特定应用集成电路。</li>
</ul>
<p>虽然这些内部开发的芯片在某些方面可能超越英伟达的 Hopper 和/或 Blackwell，但后者的硬件在计算能力方面仍应保持明显的优势。然而，这可能不足以阻止英伟达在未来几个季度失去宝贵的数据中心空间。</p>
<p>微软、Meta、亚马逊和 Alphabet 的财力雄厚，运营现金流充足。虽然他们都能承受英伟达 AI-GPU 的高价，但这并不意味着他们愿意为这款硬件支付更高的价格。与英伟达芯片相关的订单积压，加上使用内部开发的 AI-GPU 的便利性和成本，将可能导致英伟达在未来失去数据中心空间。</p>
<p>请记住，AI-GPU 的稀缺性一直是推动英伟达卓越定价能力的主要催化剂。随着其顶级客户开发自己的硬件，这种稀缺性迟早会减弱，英伟达的利润率也会随之下降。</p>
<p>内部竞争无疑是对英伟达 AI 主导地位最大的威胁。</p>

微软

亚马逊

<p>Nvidia 已成为人工智能市场的领导者，其 GPU 在数据中心占据主导地位，并因强劲的需求而价格高昂。然而，该公司面临着重大威胁，不仅来自于像 AMD 这样的外部竞争对手，更重要的是来自内部竞争，因为微软和亚马逊等主要客户开始开发自己的人工智能解决方案。这可能会挑战 Nvidia 的市场地位和增长轨迹，尽管其销售和增长率令人印象深刻</p>

<p>Roughly three decades ago, the advent of the internet changed everything for corporate America. Although it took many years for the internet to mature as a technology, and for companies to realize its full potential, it's positively altered the growth trajectory for businesses and opened new doors that previously hadn't existed.</p>
<div class="lb-trans"><p>大约三十年前，互联网的出现改变了美国企业的一切。尽管互联网作为一项技术成熟需要许多年，企业也需要时间来意识到其全部潜力，但它积极地改变了商业的增长轨迹，并打开了以前不存在的新机遇。</p>
</div><p>Since the mid-1990s, Wall Street has been waiting for a new technology or game-changing innovation to replicate what the internet did for businesses. Artificial intelligence (AI) appears to have answered the call.</p>
<div class="lb-trans"><p>自 1990 年代中期以来，华尔街一直在等待一种新技术或颠覆性创新，以复制互联网对商业的影响。人工智能（AI）似乎回应了这一呼唤。</p>
</div><p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy83OTc1MDIvYXJ0aWZpY2lhbC1pbnRlbGxpZ2VuY2UtYWktcm9ib3QtYmlnLWRhdGEtYnVsbC1tYXJrZXQtc3RvY2stY2hhcnQtZ2V0dHkuanBnJnc9NzAw" alt="" original-src="https://g.foolcdn.com/image/?url=https%3A%2F%2Fg.foolcdn.com%2Feditorial%2Fimages%2F797502%2Fartificial-intelligence-ai-robot-big-data-bull-market-stock-chart-getty.jpg&amp;op=resize&amp;w=700"/></p>
<p>Image source: Getty Images.</p>
<div class="lb-trans"><p>图片来源：Getty Images。</p>
</div><p>What makes AI such an intriguing technology is its broad-reaching utility. AI-driven software and systems have the capacity grow smarter and become more efficient at their assigned tasks over time. What's more, software and systems may be able to learn new tasks without human intervention.</p>
<div class="lb-trans"><p>人工智能之所以成为如此引人注目的技术，是因为它的广泛实用性。基于人工智能的软件和系统有能力随着时间的推移变得更加智能和高效。此外，这些软件和系统可能能够在没有人类干预的情况下学习新任务。</p>
</div><p>To some, the sky is truly the limit for artificial intelligence. In <em>Sizing the Prize</em>, the analysts at PwC predict AI will increase global gross domestic product by $15.7 trillion come 2030, with these gains coming from a combination of increased productivity and consumption-side effects.</p>
<div class="lb-trans"><p>对一些人来说，人工智能的潜力真的是无穷无尽。在《Sizing the Prize》中，普华永道的分析师预测，到 2030 年，人工智能将使全球国内生产总值增加 15.7 万亿美元，这些增长将来自生产力的提高和消费侧效应的结合。</p>
</div><p>A $15.7 trillion addressable market leaves plenty of room for multiple companies to be winners. But over the past two years, there's been no clearer beneficiary of the AI revolution than semiconductor colossus <strong>Nvidia</strong>(NVDA 0.34%), which vaulted from a $360 billion market cap to end 2022 to $3.56 trillion, as of the closing bell on Nov. 11.</p>
<div class="lb-trans"><p>一个 15.7 万亿美元的可寻址市场为多家公司提供了获胜的空间。但在过去两年中，半导体巨头 <strong>Nvidia</strong>（NVDA 0.34%）无疑是人工智能革命中最明显的受益者，其市值从 2022 年底的 3600 亿美元飙升至截至 11 月 11 日的 3.56 万亿美元。</p>
</div><h2>Nvidia's operating expansion has been virtually flawless</h2>
<div class="lb-trans"><h2>Nvidia 的运营扩展几乎无可挑剔</h2>
</div><p>Investors don't have to look far to discover why Nvidia has become Wall Street's most-valuable publicly traded company. Its graphics processing units (GPUs) have become the preferred choice of businesses operating AI-accelerated data centers. Nvidia's H100 GPU, commonly known as the &#34;Hopper,&#34; and successor Blackwell GPU architecture, are effectively the brains that allow for split-second decision-making by AI software and systems.</p>
<div class="lb-trans"><p>投资者无需远行就能发现 Nvidia 为何成为华尔街最有价值的上市公司。其图形处理单元（GPU）已成为运营人工智能加速数据中心的企业的首选。Nvidia 的 H100 GPU，通常被称为 “Hopper”，以及其后继的 Blackwell GPU 架构，实际上是使人工智能软件和系统能够进行瞬时决策的 “大脑”。</p>
</div><p>Based on a study from the analysts at TechInsights, Nvidia accounted for roughly 98% of the 2.67 million GPUs shipped to data centers in 2022, as well as the 3.85 million GPUs shipped in 2023. It's unlikely to lose its near-monopoly market share this year, either, with orders for the Hopper chip and Blackwell backlogged.</p>
<div class="lb-trans"><p>根据 TechInsights 分析师的研究，Nvidia 在 2022 年向数据中心出货的 267 万 GPU 中占据了约 98% 的份额，以及在 2023 年出货的 385 万 GPU。预计今年它也不太可能失去其近乎垄断的市场份额，Hopper 芯片和 Blackwell 的订单已经积压。</p>
</div><p>This is a good time to mention that when demand for a good or service outstrips supply, the price of that good or service often rises. Nvidia has been able to command $30,000 to $40,000 for the Hopper, which is 100% to 300% more than what competing AI-GPUs cost. Businesses have been willing to pay this premium given the computing advantages offered by Nvidia's hardware, and it's translated into a sizable uptick in the company's gross margin.</p>
<div class="lb-trans"><p>此时提到，当对某种商品或服务的需求超过供应时，该商品或服务的价格往往会上涨。Nvidia 能够以 30,000 到 40,000 美元的价格出售 Hopper，这比竞争对手的人工智能 GPU 价格高出 100% 到 300%。鉴于 Nvidia 硬件所提供的计算优势，企业愿意支付这一溢价，这也转化为公司毛利率的显著提升。</p>
</div><p>The company's CUDA platform also deserves credit for its virtually flawless operating expansion. CUDA is the software toolkit developers use to get the most out of their GPUs, including building large language models (LLMs). It's playing a key role in keeping Nvidia's clients loyal to the company's ecosystem of solutions.</p>
<div class="lb-trans"><p>公司的 CUDA 平台也应为其几乎无可挑剔的运营扩展而受到赞誉。CUDA 是开发者用来充分利用其 GPU 的软件工具包，包括构建大型语言模型（LLM）。它在保持 Nvidia 客户忠诚于公司解决方案生态系统方面发挥了关键作用。</p>
</div><p>Lastly, investors have been mesmerized by never-before-seen growth rates from a market-leading company. When fiscal 2023 came to a close on Jan. 29, 2023, Nvidia reported $27 billion in full-year sales. But based on Wall Street's forecast for fiscal 2026, Nvidia is on track to deliver $180 billion in revenue. That's a three-year compound annual sales growth rate of about 88%!</p>
<div class="lb-trans"><p>最后，投资者被市场领先公司前所未见的增长率所吸引。当 2023 财年于 2023 年 1 月 29 日结束时，Nvidia 报告全年销售额为 270 亿美元。但根据华尔街对 2026 财年的预测，Nvidia 有望实现 1800 亿美元的收入。这是三年复合年销售增长率约为 88%！</p>
</div><p>Yet in spite of its nearly textbook operating expansion, one undeniable threat looms large for Nvidia -- and pretty much no one is talking about it.</p>
<div class="lb-trans"><p>然而，尽管其运营扩展几乎教科书般完美，但对 Nvidia 来说，有一个不可否认的威胁正在逼近——而几乎没有人谈论它。</p>
</div><p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy83OTc1MDIvYXJ0aWZpY2lhbC1pbnRlbGxpZ2VuY2UtYWktY2hpcC1udmlkaWEtZ3B1LWRhdGEtY2VudGVyLWdldHR5LmpwZyZ3PTcwMA" alt="" original-src="https://g.foolcdn.com/image/?url=https%3A%2F%2Fg.foolcdn.com%2Feditorial%2Fimages%2F797502%2Fartificial-intelligence-ai-chip-nvidia-gpu-data-center-getty.jpg&amp;op=resize&amp;w=700"/></p>
<p>Image source: Getty Images.</p>
<div class="lb-trans"><p>图片来源：Getty Images。</p>
</div><h2>This threat has the potential to knock Wall Street's AI darling off of its pedestal</h2>
<div class="lb-trans"><h2>这个威胁有可能将华尔街的人工智能宠儿拉下神坛</h2>
</div><p>As most investors are probably well aware, the jaw-dropping addressable market for artificial intelligence has businesses clamoring for their piece of the pie. In the coming quarters, Nvidia is going to face no shortage of external competition.</p>
<div class="lb-trans"><p>正如大多数投资者可能已经意识到的，人工智能的惊人可寻址市场使企业争相分一杯羹。在接下来的几个季度中，Nvidia 将面临外部竞争的压力。</p>
</div><p>Even though <strong>Advanced Micro Devices</strong>(AMD -0.33%) entered the scene after Nvidia, it's had no trouble ramping up production for its MI300X AI-GPU. AMD also recently introduced its next-gen chip, the MI325X, which is expected to go into production before the end of this year. AMD's chips have a decisively lower price point than Nvidia's Hopper and Blackwell, which may make them attractive for businesses wanting to leverage AI in their data centers.</p>
<div class="lb-trans"><p>尽管 <strong>Advanced Micro Devices</strong>（AMD -0.33%）在 Nvidia 之后进入市场，但它在 MI300X 人工智能 GPU 的生产上没有遇到任何困难。AMD 最近还推出了其下一代芯片 MI325X，预计将在今年年底前投入生产。AMD 的芯片价格明显低于 Nvidia 的 Hopper 和 Blackwell，这可能使它们对希望在数据中心利用人工智能的企业具有吸引力。</p>
</div><p>However, external competition isn't the greatest threat to dethrone Nvidia. Rather, the biggest immediate headwind for Nvidia is <em>internal</em> competition.</p>
<div class="lb-trans"><p>然而，外部竞争并不是推翻 Nvidia 的最大威胁。相反，Nvidia 面临的最大直接阻力是内部竞争。</p>
</div><p>Many of America's most-influential businesses have ordered and are using Nvidia's GPUs in their high-compute data centers. This includes <strong>Microsoft</strong>(MSFT 0.40%), <strong>Meta Platforms</strong>(META -0.49%), <strong>Amazon</strong>(AMZN -1.22%), <strong>Alphabet</strong>(GOOGL -1.85%) (GOOG -1.74%), <strong>Tesla</strong>, OpenAI, and AI infrastructure kingpin <strong>Super Micro Computer</strong>, which incorporates Nvidia's GPUs into its customizable rack servers.</p>
<div class="lb-trans"><p>许多美国最具影响力的企业已经订购并在其高计算数据中心中使用 Nvidia 的 GPU。这包括 <strong>Microsoft</strong>（MSFT 0.40%）、<strong>Meta Platforms</strong>（META -0.49%）、<strong>Amazon</strong>（AMZN -1.22%）、<strong>Alphabet</strong>（GOOGL -1.85%）（GOOG -1.74%）、<strong>Tesla</strong>、OpenAI，以及将 Nvidia 的 GPU 集成到其可定制机架服务器中的人工智能基础设施巨头 <strong>Super Micro Computer</strong>。</p>
</div><p>For the three months ended July 28, 2024, four of Nvidia's customers -- it doesn't disclose the name of its top customers -- accounted for 46% of its net sales, with a fifth contributing less than 10%, but still likely in the high single digits. We can comfortably say that half of Nvidia's revenue comes from just five customers. If I had to venture a guess, I'd expect to these clients to be Microsoft, Meta, Amazon, Alphabet, and Super Micro (not in this order).</p>
<div class="lb-trans"><p>截至 2024 年 7 月 28 日的三个月内，Nvidia 的四个客户——它并未披露其主要客户的名称——占其净销售额的 46%，第五个客户贡献不到 10%，但仍可能在高个位数范围内。我们可以自信地说，Nvidia 的一半收入来自仅五个客户。如果我必须猜测，我会认为这些客户是 Microsoft、Meta、Amazon、Alphabet 和 Super Micro（不按此顺序）。</p>
</div><p><img src="https://imageproxy.pbkrs.com/https://media.ycharts.com/charts/ef803252949883618de7b1017753a00c.png" alt="" original-src="https://media.ycharts.com/charts/ef803252949883618de7b1017753a00c.png"/></p>
<p>AI-GPU scarcity has sent Nvidia's gross margin soaring. NVDA Gross Profit Margin (Quarterly) data by YCharts.</p>
<div class="lb-trans"><p>人工智能 GPU 的稀缺性使 Nvidia 的毛利率飙升。NVDA 毛利率（季度）数据来自 YCharts。</p>
</div><p>The concern for Nvidia is that most of these top customers are developing AI-GPUs for use in their respective data centers.</p>
<div class="lb-trans"><p>对英伟达的担忧在于，这些顶级客户大多数正在为各自的数据中心开发 AI-GPU。</p>
</div><ul>
<li>Microsoft developed the Azure Maia AI chip, which can be used to train large language models and oversee generative AI solutions within the company's Azure cloud infrastructure platform.</li>
<li>Meta is working internally on developing the &#34;Meta Training and Inference Accelerator&#34; chip to maximize the potential of its AI data center.</li>
<li>Amazon is developing a number of GPU chips, including Trainium2 and Inferentia, which will cater to clients of its world-leading cloud infrastructure service platform, Amazon Web Services (AWS).</li>
<li>Alphabet is relying on tensor processing units (TPUs) for training LLMs and inference. TPUs are application-specific integrated circuits custom-built for AI applications.</li>
</ul>
<div class="lb-trans"><ul>
<li>微软开发了 Azure Maia AI 芯片，可以用于训练大型语言模型并监督公司 Azure 云基础设施平台内的生成式 AI 解决方案。</li>
<li>Meta 正在内部开发 “Meta 训练与推理加速器” 芯片，以最大化其 AI 数据中心的潜力。</li>
<li>亚马逊正在开发多款 GPU 芯片，包括 Trainium2 和 Inferentia，旨在满足其全球领先的云基础设施服务平台 Amazon Web Services (AWS) 的客户需求。</li>
<li>Alphabet 依赖张量处理单元（TPU）来训练大型语言模型和进行推理。TPU 是为 AI 应用量身定制的特定应用集成电路。</li>
</ul>
</div><p>While there might be various aspects of these internally developed chips that outperform Nvidia's Hopper and/or Blackwell, the latter's hardware should remain decisively superior with regard to its computing capabilities. However, this may not be enough to keep Nvidia from losing valuable data center real estate in the quarters to come.</p>
<div class="lb-trans"><p>虽然这些内部开发的芯片在某些方面可能超越英伟达的 Hopper 和/或 Blackwell，但后者的硬件在计算能力方面仍应保持明显的优势。然而，这可能不足以阻止英伟达在未来几个季度失去宝贵的数据中心空间。</p>
</div><p>Microsoft, Meta, Amazon, and Alphabet have very deep pockets and abundant operating cash flow. While they can all afford Nvidia's premium price point for its AI-GPUs, it doesn't mean they're satisfied paying a considerably higher price point for this hardware. The order backlog associated with Nvidia's chips, coupled with the ease and cost of using internally developed AI-GPUs, will likely cause Nvidia to lose data center space in the future.</p>
<div class="lb-trans"><p>微软、Meta、亚马逊和 Alphabet 的财力雄厚，运营现金流充足。虽然他们都能承受英伟达 AI-GPU 的高价，但这并不意味着他们愿意为这款硬件支付更高的价格。与英伟达芯片相关的订单积压，加上使用内部开发的 AI-GPU 的便利性和成本，将可能导致英伟达在未来失去数据中心空间。</p>
</div><p>Remember, AI-GPU scarcity has been the leading catalyst that's driven Nvidia's exceptional pricing power. With its top customers developing hardware of their own, it's only a matter of time before this scarcity wanes and Nvidia's margins weaken.</p>
<div class="lb-trans"><p>请记住，AI-GPU 的稀缺性一直是推动英伟达卓越定价能力的主要催化剂。随着其顶级客户开发自己的硬件，这种稀缺性迟早会减弱，英伟达的利润率也会随之下降。</p>
</div><p>Internal competition is, by far, the biggest threat to Nvidia's AI dominance.</p>
<div class="lb-trans"><p>内部竞争无疑是对英伟达 AI 主导地位最大的威胁。</p>
</div>

This Is the Biggest Threat to Nvidia's Artificial Intelligence (AI) Dominance That Virtually No One Is Talking About

- 人工智能被视为继互联网之后的下一个颠覆性技术。  
- Nvidia 在 AI-GPU 市场中占据主导地位，2022 年出货量占比达 98%。  
- 然而，微软、亚马逊等客户正在开发自有 AI-GPU，可能威胁 Nvidia 的市场份额。  

这是几乎无人提及的对 Nvidia 人工智能（AI）主导地位的最大威胁