<p>大約三十年前，互聯網的出現改變了美國企業的一切。儘管互聯網作為一項技術成熟需要許多年，企業也需要時間來意識到其全部潛力，但它積極地改變了商業的增長軌跡，並打開了以前不存在的新機遇。</p>
<p>自 1990 年代中期以來，華爾街一直在等待一種新技術或顛覆性創新，以複製互聯網對商業的影響。人工智能（AI）似乎回應了這一呼喚。</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>圖片來源：Getty Images。</p>
<p>人工智能之所以成為如此引人注目的技術，是因為它的廣泛實用性。基於人工智能的軟件和系統有能力隨着時間的推移變得更加智能和高效。此外，這些軟件和系統可能能夠在沒有人類干預的情況下學習新任務。</p>
<p>對一些人來説，人工智能的潛力真的是無窮無盡。在《Sizing the Prize》中，普華永道的分析師預測，到 2030 年，人工智能將使全球國內生產總值增加 15.7 萬億美元，這些增長將來自生產力的提高和消費側效應的結合。</p>
<p>一個 15.7 萬億美元的可尋址市場為多家公司提供了獲勝的空間。但在過去兩年中，半導體巨頭 <strong>Nvidia</strong>（NVDA 0.34%）無疑是人工智能革命中最明顯的受益者，其市值從 2022 年底的 3600 億美元飆升至截至 11 月 11 日的 3.56 萬億美元。</p>
<h2>Nvidia 的運營擴展幾乎無可挑剔</h2>
<p>投資者無需遠行就能發現 Nvidia 為何成為華爾街最有價值的上市公司。其圖形處理單元（GPU）已成為運營人工智能加速數據中心的企業的首選。Nvidia 的 H100 GPU，通常被稱為 “Hopper”，以及其後繼的 Blackwell GPU 架構，實際上是使人工智能軟件和系統能夠進行瞬時決策的 “大腦”。</p>
<p>根據 TechInsights 分析師的研究，Nvidia 在 2022 年向數據中心出貨的 267 萬 GPU 中佔據了約 98% 的份額，以及在 2023 年出貨的 385 萬 GPU。預計今年它也不太可能失去其近乎壟斷的市場份額，Hopper 芯片和 Blackwell 的訂單已經積壓。</p>
<p>此時提到，當對某種商品或服務的需求超過供應時，該商品或服務的價格往往會上漲。Nvidia 能夠以 30,000 到 40,000 美元的價格出售 Hopper，這比競爭對手的人工智能 GPU 價格高出 100% 到 300%。鑑於 Nvidia 硬件所提供的計算優勢，企業願意支付這一溢價，這也轉化為公司毛利率的顯著提升。</p>
<p>公司的 CUDA 平台也應為其幾乎無可挑剔的運營擴展而受到讚譽。CUDA 是開發者用來充分利用其 GPU 的軟件工具包，包括構建大型語言模型（LLM）。它在保持 Nvidia 客户忠誠於公司解決方案生態系統方面發揮了關鍵作用。</p>
<p>最後，投資者被市場領先公司前所未見的增長率所吸引。當 2023 財年於 2023 年 1 月 29 日結束時，Nvidia 報告全年銷售額為 270 億美元。但根據華爾街對 2026 財年的預測，Nvidia 有望實現 1800 億美元的收入。這是三年複合年銷售增長率約為 88%！</p>
<p>然而，儘管其運營擴展幾乎教科書般完美，但對 Nvidia 來説，有一個不可否認的威脅正在逼近——而幾乎沒有人談論它。</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>圖片來源：Getty Images。</p>
<h2>這個威脅有可能將華爾街的人工智能寵兒拉下神壇</h2>
<p>正如大多數投資者可能已經意識到的，人工智能的驚人可尋址市場使企業爭相分一杯羹。在接下來的幾個季度中，Nvidia 將面臨外部競爭的壓力。</p>
<p>儘管 <strong>Advanced Micro Devices</strong>（AMD -0.33%）在 Nvidia 之後進入市場，但它在 MI300X 人工智能 GPU 的生產上沒有遇到任何困難。AMD 最近還推出了其下一代芯片 MI325X，預計將在今年年底前投入生產。AMD 的芯片價格明顯低於 Nvidia 的 Hopper 和 Blackwell，這可能使它們對希望在數據中心利用人工智能的企業具有吸引力。</p>
<p>然而，外部競爭並不是推翻 Nvidia 的最大威脅。相反，Nvidia 面臨的最大直接阻力是內部競爭。</p>
<p>許多美國最具影響力的企業已經訂購併在其高計算數據中心中使用 Nvidia 的 GPU。這包括 <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，以及將 Nvidia 的 GPU 集成到其可定製機架服務器中的人工智能基礎設施巨頭 <strong>Super Micro Computer</strong>。</p>
<p>截至 2024 年 7 月 28 日的三個月內，Nvidia 的四個客户——它並未披露其主要客户的名稱——佔其淨銷售額的 46%，第五個客户貢獻不到 10%，但仍可能在高個位數範圍內。我們可以自信地説，Nvidia 的一半收入來自僅五個客户。如果我必須猜測，我會認為這些客户是 Microsoft、Meta、Amazon、Alphabet 和 Super Micro（不按此順序）。</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 的毛利率飆升。NVDA 毛利率（季度）數據來自 YCharts。</p>
<p>對英偉達的擔憂在於，這些頂級客户大多數正在為各自的數據中心開發 AI-GPU。</p>
<ul>
<li>微軟開發了 Azure Maia AI 芯片，可以用於訓練大型語言模型並監督公司 Azure 雲基礎設施平台內的生成式 AI 解決方案。</li>
<li>Meta 正在內部開發 “Meta 訓練與推理加速器” 芯片，以最大化其 AI 數據中心的潛力。</li>
<li>亞馬遜正在開發多款 GPU 芯片，包括 Trainium2 和 Inferentia，旨在滿足其全球領先的雲基礎設施服務平台 Amazon Web Services (AWS) 的客户需求。</li>
<li>Alphabet 依賴張量處理單元（TPU）來訓練大型語言模型和進行推理。TPU 是為 AI 應用量身定製的特定應用集成電路。</li>
</ul>
<p>雖然這些內部開發的芯片在某些方面可能超越英偉達的 Hopper 和/或 Blackwell，但後者的硬件在計算能力方面仍應保持明顯的優勢。然而，這可能不足以阻止英偉達在未來幾個季度失去寶貴的數據中心空間。</p>
<p>微軟、Meta、亞馬遜和 Alphabet 的財力雄厚，運營現金流充足。雖然他們都能承受英偉達 AI-GPU 的高價，但這並不意味着他們願意為這款硬件支付更高的價格。與英偉達芯片相關的訂單積壓，加上使用內部開發的 AI-GPU 的便利性和成本，將可能導致英偉達在未來失去數據中心空間。</p>
<p>請記住，AI-GPU 的稀缺性一直是推動英偉達卓越定價能力的主要催化劑。隨着其頂級客户開發自己的硬件，這種稀缺性遲早會減弱，英偉達的利潤率也會隨之下降。</p>
<p>內部競爭無疑是對英偉達 AI 主導地位最大的威脅。</p>

微軟

亞馬遜

<p>Nvidia 已成為人工智能市場的領導者，其 GPU 在數據中心佔據主導地位，並因強勁的需求而價格高昂。然而，該公司面臨着重大威脅，不僅來自於像 AMD 這樣的外部競爭對手，更重要的是來自內部競爭，因為微軟和亞馬遜等主要客户開始開發自己的人工智能解決方案。這可能會挑戰 Nvidia 的市場地位和增長軌跡，儘管其銷售和增長率令人印象深刻</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>大約三十年前，互聯網的出現改變了美國企業的一切。儘管互聯網作為一項技術成熟需要許多年，企業也需要時間來意識到其全部潛力，但它積極地改變了商業的增長軌跡，並打開了以前不存在的新機遇。</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 年代中期以來，華爾街一直在等待一種新技術或顛覆性創新，以複製互聯網對商業的影響。人工智能（AI）似乎回應了這一呼喚。</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>圖片來源：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>人工智能之所以成為如此引人注目的技術，是因為它的廣泛實用性。基於人工智能的軟件和系統有能力隨着時間的推移變得更加智能和高效。此外，這些軟件和系統可能能夠在沒有人類干預的情況下學習新任務。</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>對一些人來説，人工智能的潛力真的是無窮無盡。在《Sizing the Prize》中，普華永道的分析師預測，到 2030 年，人工智能將使全球國內生產總值增加 15.7 萬億美元，這些增長將來自生產力的提高和消費側效應的結合。</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>一個 15.7 萬億美元的可尋址市場為多家公司提供了獲勝的空間。但在過去兩年中，半導體巨頭 <strong>Nvidia</strong>（NVDA 0.34%）無疑是人工智能革命中最明顯的受益者，其市值從 2022 年底的 3600 億美元飆升至截至 11 月 11 日的 3.56 萬億美元。</p>
</div><h2>Nvidia's operating expansion has been virtually flawless</h2>
<div class="lb-trans"><h2>Nvidia 的運營擴展幾乎無可挑剔</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>投資者無需遠行就能發現 Nvidia 為何成為華爾街最有價值的上市公司。其圖形處理單元（GPU）已成為運營人工智能加速數據中心的企業的首選。Nvidia 的 H100 GPU，通常被稱為 “Hopper”，以及其後繼的 Blackwell GPU 架構，實際上是使人工智能軟件和系統能夠進行瞬時決策的 “大腦”。</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>根據 TechInsights 分析師的研究，Nvidia 在 2022 年向數據中心出貨的 267 萬 GPU 中佔據了約 98% 的份額，以及在 2023 年出貨的 385 萬 GPU。預計今年它也不太可能失去其近乎壟斷的市場份額，Hopper 芯片和 Blackwell 的訂單已經積壓。</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>此時提到，當對某種商品或服務的需求超過供應時，該商品或服務的價格往往會上漲。Nvidia 能夠以 30,000 到 40,000 美元的價格出售 Hopper，這比競爭對手的人工智能 GPU 價格高出 100% 到 300%。鑑於 Nvidia 硬件所提供的計算優勢，企業願意支付這一溢價，這也轉化為公司毛利率的顯著提升。</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 平台也應為其幾乎無可挑剔的運營擴展而受到讚譽。CUDA 是開發者用來充分利用其 GPU 的軟件工具包，包括構建大型語言模型（LLM）。它在保持 Nvidia 客户忠誠於公司解決方案生態系統方面發揮了關鍵作用。</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>最後，投資者被市場領先公司前所未見的增長率所吸引。當 2023 財年於 2023 年 1 月 29 日結束時，Nvidia 報告全年銷售額為 270 億美元。但根據華爾街對 2026 財年的預測，Nvidia 有望實現 1800 億美元的收入。這是三年複合年銷售增長率約為 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，儘管其運營擴展幾乎教科書般完美，但對 Nvidia 來説，有一個不可否認的威脅正在逼近——而幾乎沒有人談論它。</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>圖片來源：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>這個威脅有可能將華爾街的人工智能寵兒拉下神壇</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>正如大多數投資者可能已經意識到的，人工智能的驚人可尋址市場使企業爭相分一杯羹。在接下來的幾個季度中，Nvidia 將面臨外部競爭的壓力。</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>儘管 <strong>Advanced Micro Devices</strong>（AMD -0.33%）在 Nvidia 之後進入市場，但它在 MI300X 人工智能 GPU 的生產上沒有遇到任何困難。AMD 最近還推出了其下一代芯片 MI325X，預計將在今年年底前投入生產。AMD 的芯片價格明顯低於 Nvidia 的 Hopper 和 Blackwell，這可能使它們對希望在數據中心利用人工智能的企業具有吸引力。</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，外部競爭並不是推翻 Nvidia 的最大威脅。相反，Nvidia 面臨的最大直接阻力是內部競爭。</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>許多美國最具影響力的企業已經訂購併在其高計算數據中心中使用 Nvidia 的 GPU。這包括 <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，以及將 Nvidia 的 GPU 集成到其可定製機架服務器中的人工智能基礎設施巨頭 <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 日的三個月內，Nvidia 的四個客户——它並未披露其主要客户的名稱——佔其淨銷售額的 46%，第五個客户貢獻不到 10%，但仍可能在高個位數範圍內。我們可以自信地説，Nvidia 的一半收入來自僅五個客户。如果我必須猜測，我會認為這些客户是 Microsoft、Meta、Amazon、Alphabet 和 Super Micro（不按此順序）。</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 的毛利率飆升。NVDA 毛利率（季度）數據來自 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>對英偉達的擔憂在於，這些頂級客户大多數正在為各自的數據中心開發 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>微軟開發了 Azure Maia AI 芯片，可以用於訓練大型語言模型並監督公司 Azure 雲基礎設施平台內的生成式 AI 解決方案。</li>
<li>Meta 正在內部開發 “Meta 訓練與推理加速器” 芯片，以最大化其 AI 數據中心的潛力。</li>
<li>亞馬遜正在開發多款 GPU 芯片，包括 Trainium2 和 Inferentia，旨在滿足其全球領先的雲基礎設施服務平台 Amazon Web Services (AWS) 的客户需求。</li>
<li>Alphabet 依賴張量處理單元（TPU）來訓練大型語言模型和進行推理。TPU 是為 AI 應用量身定製的特定應用集成電路。</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>雖然這些內部開發的芯片在某些方面可能超越英偉達的 Hopper 和/或 Blackwell，但後者的硬件在計算能力方面仍應保持明顯的優勢。然而，這可能不足以阻止英偉達在未來幾個季度失去寶貴的數據中心空間。</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>微軟、Meta、亞馬遜和 Alphabet 的財力雄厚，運營現金流充足。雖然他們都能承受英偉達 AI-GPU 的高價，但這並不意味着他們願意為這款硬件支付更高的價格。與英偉達芯片相關的訂單積壓，加上使用內部開發的 AI-GPU 的便利性和成本，將可能導致英偉達在未來失去數據中心空間。</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>請記住，AI-GPU 的稀缺性一直是推動英偉達卓越定價能力的主要催化劑。隨着其頂級客户開發自己的硬件，這種稀缺性遲早會減弱，英偉達的利潤率也會隨之下降。</p>
</div><p>Internal competition is, by far, the biggest threat to Nvidia's AI dominance.</p>
<div class="lb-trans"><p>內部競爭無疑是對英偉達 AI 主導地位最大的威脅。</p>
</div>

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

- 人工智能被視為繼互聯網之後的下一個顛覆性技術。  
- Nvidia 在 AI-GPU 市場中佔據主導地位，2022 年出貨量佔比達 98%。  
- 然而，微軟、亞馬遜等客户正在開發自有 AI-GPU，可能威脅 Nvidia 的市場份額。  

這是幾乎無人提及的對 Nvidia 人工智能（AI）主導地位的最大威脅