<p>在設計用於支持人工智能（AI）工作負載的半導體芯片時，有兩家公司遠遠領先於其他公司：<strong>英偉達</strong>（Nvidia）（NVDA -4.36%）和 <strong>博通</strong>（Broadcom）（AVGO -2.53%）。英偉達在 AI 芯片領域是最大的早期贏家，但博通正在逐漸獲得動力。</p>
<p>讓我們看看在當前市場拋售期間，投資者應該關注哪隻股票。</p>
<h2>兩種不同的策略</h2>
<p>英偉達和博通在 AI 芯片市場採取了兩種截然不同的策略。英偉達在圖形處理單元（GPU）方面是明顯的市場領導者，市場份額超過 80%。GPU 最初是為了加速視頻遊戲中的圖形渲染而設計的，但由於其快速的處理能力，它們已成為支持 AI 工作負載的主要芯片。</p>
<p>英偉達巨大市場份額的秘密在於其 CUDA 軟件平台。它是第一個允許開發者將 GPU 編程用於超出其原始用途的任務的軟件平台，使其成為開發者學習編程 GPU 的標準。從那時起，該公司在 CUDA 之上構建了一系列庫和工具，稱為 CUDA X，幫助提高 AI 模型訓練的效率和可擴展性，並改善推理時間。</p>
<p>另一方面，博通幫助其客户開發稱為應用特定集成電路（ASIC）的定製 AI 芯片。ASIC 是為非常特定的任務設計的。因此，這些芯片的性能更好，功耗低於大眾市場的 GPU。缺點是開發這些定製芯片需要相當長的時間，並且前期成本也很高。它們也沒有 GPU 那種可以編程用於多種任務的靈活性。</p>
<p>毫不奇怪，在 AI 基礎設施建設的初期階段，英偉達的 GPU 是超大規模數據中心運營商（hyperscalers）用於訓練 AI 模型和構建數據中心基礎設施以滿足強勁需求的最常用芯片。畢竟，大眾市場的 GPU 更容易獲得，而英偉達的 CUDA 軟件平台使它們能夠輕鬆編程以完成手頭的任務。</p>
<p>然而，隨着英偉達 GPU 價格因其主導市場地位而飆升，越來越多的公司開始在博通的幫助下設計自己的 AI 定製芯片。<strong>字母表</strong>（Alphabet）是該公司的第一個定製 AI 芯片客户，博通幫助其開發了用於 Google Cloud 業務的張量處理單元（TPU）。這些芯片專門設計用於優化 Google Cloud 的 TensorFlow 框架中的 AI 工作負載。字母表已將其歸功於提高性能，並因其較低的功耗而降低了運營成本。</p>
<p>博通逐漸獲得了更多的定製 AI 芯片客户。<strong>Meta Platforms</strong> 和 OpenAI 據報道是與博通合作開發 AI 芯片的下一家公司。博通預測，這三位客户在 2027 財年（截至 2027 年 10 月）將有價值在 600 億美元到 900 億美元之間的可服務市場機會。目前，博通的年度 AI 收入運行率剛剛超過 160 億美元，顯示出顯著的增長潛力。</p>
<p>與此同時，該公司在最初的三位客户之外增加了額外的定製 AI 芯片客户。<strong>蘋果</strong>（Apple）和抖音母公司字節跳動（ByteDance）被廣泛認為是其開發進展最為順利的下兩位客户。字母表從設計到生產其芯片大約花費了 15 個月，這為這些客户成為重要收入貢獻者提供了一個大致的時間框架。博通還暗示了另外兩位定製 AI 芯片客户。</p>
<p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84MTUwNjEvZ2V0dHlpbWFnZXMtMTM2NDg1OTcyMi5qcGcmdz03MDA?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-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84MTUwNjEvZ2V0dHlpbWFnZXMtMTM2NDg1OTcyMi5qcGcmdz03MDA"/></p>
<p>圖片來源：Getty Images。</p>
<h2>哪隻股票更值得購買？</h2>
<p>從估值的角度來看，這兩家公司在未來的市盈率（P/E）倍數上相似，英偉達為 21.5 倍，博通為 23 倍。雖然英偉達面前仍有強大的機會，但博通似乎在未來的增長前景更強。</p>
<p>部分原因是大數法則，因為英偉達在過去兩年中已經將其收入增長了超過 380%。與此同時，博通在 AI 芯片領域也取得了強勁的進展。考慮到設計定製芯片所需的時間和前期成本，博通的客户將會在大型項目中使用這些芯片。</p>
<p>我認為這兩家公司都將繼續贏得其在 AI 芯片市場的合理份額，並且都將看到穩健的增長。然而，考慮到博通面前的巨大機會，我在當前水平上更偏好博通的股票。當然，在現實世界中，您應該能夠長期持有這兩者。</p>

英偉達

博通

<p>英偉達和博通是人工智能芯片市場的領先者，各自採取不同的策略。英偉達在 GPU 市場佔據超過 80% 的市場份額，利用其 CUDA 軟件平台來處理 AI 工作負載。相比之下，博通專注於為特定任務定製的人工智能芯片（ASIC），並在 Alphabet、Meta 和 OpenAI 等客户中獲得了關注。雖然兩家公司有類似的市盈率，但博通因其不斷擴大的客户基礎和顯著的市場機會，被認為具有更強的增長前景。作者更看好博通的股票，認為其潛力巨大，儘管預計兩家公司在人工智能芯片領域都將蓬勃發展</p>

<p>When it comes to designing semiconductor chips used to power artificial intelligence (AI) workloads, two companies stand head and shoulders above the rest: <strong>Nvidia</strong>(NVDA -4.36%) and <strong>Broadcom</strong>(AVGO -2.53%). Nvidia has been the biggest early winner in AI chips, but Broadcom has been gaining momentum.</p>
<div class="lb-trans"><p>在設計用於支持人工智能（AI）工作負載的半導體芯片時，有兩家公司遠遠領先於其他公司：<strong>英偉達</strong>（Nvidia）（NVDA -4.36%）和 <strong>博通</strong>（Broadcom）（AVGO -2.53%）。英偉達在 AI 芯片領域是最大的早期贏家，但博通正在逐漸獲得動力。</p>
</div><p>Let's see which stock investors should look to buy during this current market sell-off.</p>
<div class="lb-trans"><p>讓我們看看在當前市場拋售期間，投資者應該關注哪隻股票。</p>
</div><h2>Two different approaches</h2>
<div class="lb-trans"><h2>兩種不同的策略</h2>
</div><p>Nvidia and Broadcom are taking two very different approaches to the AI chip market. Nvidia is the clear market leader in graphics processing units (GPUs), where it holds a more than 80% market share. GPUs were originally designed to speed up graphics rendering in video games, but due to their fast processing power, they have become the main chips used to power AI workloads.</p>
<div class="lb-trans"><p>英偉達和博通在 AI 芯片市場採取了兩種截然不同的策略。英偉達在圖形處理單元（GPU）方面是明顯的市場領導者，市場份額超過 80%。GPU 最初是為了加速視頻遊戲中的圖形渲染而設計的，但由於其快速的處理能力，它們已成為支持 AI 工作負載的主要芯片。</p>
</div><p>The secret sauce behind Nvidia's huge market share is its CUDA software platform. It was the first software platform to allow developers to program GPUs for tasks beyond their original purpose, making it the standard on which developers learned to program GPUs. Since then, the company has built a collection of libraries and tools on top of CUDA, called CUDA X, that help enhance the efficiency and scalability of training AI models and improve inference times.</p>
<div class="lb-trans"><p>英偉達巨大市場份額的秘密在於其 CUDA 軟件平台。它是第一個允許開發者將 GPU 編程用於超出其原始用途的任務的軟件平台，使其成為開發者學習編程 GPU 的標準。從那時起，該公司在 CUDA 之上構建了一系列庫和工具，稱為 CUDA X，幫助提高 AI 模型訓練的效率和可擴展性，並改善推理時間。</p>
</div><p>Broadcom, on the other hand, helps its customers develop custom AI chips called application-specific integrated circuits (ASICs). ASICs are designed for very specific tasks. As such, these chips have better performance and consume less power than mass-market GPUs. The downside is that it takes considerable time to develop these custom chips and there are a lot of upfront costs, as well. They also don't provide that same type of flexibility as GPUs, which can be programmed for a variety of tasks.</p>
<div class="lb-trans"><p>另一方面，博通幫助其客户開發稱為應用特定集成電路（ASIC）的定製 AI 芯片。ASIC 是為非常特定的任務設計的。因此，這些芯片的性能更好，功耗低於大眾市場的 GPU。缺點是開發這些定製芯片需要相當長的時間，並且前期成本也很高。它們也沒有 GPU 那種可以編程用於多種任務的靈活性。</p>
</div><p>Not surprisingly, in the initial surge of the AI infrastructure buildout, Nvidia's GPUs were the most common chips that hyperscalers (operators of large data centers) used to train AI models and build out data center infrastructure to meet strong demand. After all, mass-market GPUs were much more readily available and Nvidia's CUDA software platform made them easily programmable for the tasks at hand.</p>
<div class="lb-trans"><p>毫不奇怪，在 AI 基礎設施建設的初期階段，英偉達的 GPU 是超大規模數據中心運營商（hyperscalers）用於訓練 AI 模型和構建數據中心基礎設施以滿足強勁需求的最常用芯片。畢竟，大眾市場的 GPU 更容易獲得，而英偉達的 CUDA 軟件平台使它們能夠輕鬆編程以完成手頭的任務。</p>
</div><p>However, as Nvidia's GPU prices have skyrocketed due to its dominant market position, more and more companies have started to design their own AI custom chips with the help of Broadcom. <strong>Alphabet</strong> was the company's first custom AI chip customer, with Broadcom helping it develop its Tensor Processing Unit (TPU) for its Google Cloud business. These chips are designed specifically to optimize AI workloads within Google Cloud's TensorFlow framework. Alphabet has credited them for improving performance, as well as reducing its operating costs due to their lower power consumption.</p>
<div class="lb-trans"><p>然而，隨着英偉達 GPU 價格因其主導市場地位而飆升，越來越多的公司開始在博通的幫助下設計自己的 AI 定製芯片。<strong>字母表</strong>（Alphabet）是該公司的第一個定製 AI 芯片客户，博通幫助其開發了用於 Google Cloud 業務的張量處理單元（TPU）。這些芯片專門設計用於優化 Google Cloud 的 TensorFlow 框架中的 AI 工作負載。字母表已將其歸功於提高性能，並因其較低的功耗而降低了運營成本。</p>
</div><p>Broadcom has progressively acquired more custom AI chip customers. <strong>Meta Platforms</strong> and OpenAI are reportedly the next companies to collaborate with Broadcom in developing AI chips. Broadcom has forecast that these three customers will have a serviceable market opportunity valued between $60 billion and $90 billion for its fiscal year 2027 (ending in October 2027). Currently, Broadcom's annual AI revenue run rate stands at just over $16 billion, indicating a significant growth potential.</p>
<div class="lb-trans"><p>博通逐漸獲得了更多的定製 AI 芯片客户。<strong>Meta Platforms</strong> 和 OpenAI 據報道是與博通合作開發 AI 芯片的下一家公司。博通預測，這三位客户在 2027 財年（截至 2027 年 10 月）將有價值在 600 億美元到 900 億美元之間的可服務市場機會。目前，博通的年度 AI 收入運行率剛剛超過 160 億美元，顯示出顯著的增長潛力。</p>
</div><p>Meanwhile, the company has added additional custom AI chip customers beyond its initial three. <strong>Apple</strong> and TikTok owner ByteDance are widely believed to be its next two customers that are furthest along in their development. It took about 15 months for Alphabet to go from design to production for its chips, which gives a general time frame of how long it could take before these customers can become meaningful revenue contributors. Broadcom has also hinted at two additional custom AI chip customers.</p>
<div class="lb-trans"><p>與此同時，該公司在最初的三位客户之外增加了額外的定製 AI 芯片客户。<strong>蘋果</strong>（Apple）和抖音母公司字節跳動（ByteDance）被廣泛認為是其開發進展最為順利的下兩位客户。字母表從設計到生產其芯片大約花費了 15 個月，這為這些客户成為重要收入貢獻者提供了一個大致的時間框架。博通還暗示了另外兩位定製 AI 芯片客户。</p>
</div><p><img src="https://imageproxy.pbkrs.com/https://g.foolcdn.com/image//query-b3A9cmVzaXplJnVybD1odHRwczovL2cuZm9vbGNkbi5jb20vZWRpdG9yaWFsL2ltYWdlcy84MTUwNjEvZ2V0dHlpbWFnZXMtMTM2NDg1OTcyMi5qcGcmdz03MDA" alt="" original-src="https://g.foolcdn.com/image/?url=https%3A%2F%2Fg.foolcdn.com%2Feditorial%2Fimages%2F815061%2Fgettyimages-1364859722.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>Which is the better stock to buy?</h2>
<div class="lb-trans"><h2>哪隻股票更值得購買？</h2>
</div><p>From a valuation perspective, the companies trade at similar forward price-to-earnings (P/E) multiples of 21.5 times for Nvidia and 23 times for Broadcom. While Nvidia still has a strong opportunity in front of it, Broadcom appears to have the stronger growth prospects going forward.</p>
<div class="lb-trans"><p>從估值的角度來看，這兩家公司在未來的市盈率（P/E）倍數上相似，英偉達為 21.5 倍，博通為 23 倍。雖然英偉達面前仍有強大的機會，但博通似乎在未來的增長前景更強。</p>
</div><p>Part of this is due to the law of large numbers, as Nvidia has already grown its revenue by more than 380% over the past two years. Meanwhile, Broadcom has been making strong inroads into the AI chip space. Given the time and upfront costs involved with designing custom chips, Broadcom's customers will be using these chips for large projects.</p>
<div class="lb-trans"><p>部分原因是大數法則，因為英偉達在過去兩年中已經將其收入增長了超過 380%。與此同時，博通在 AI 芯片領域也取得了強勁的進展。考慮到設計定製芯片所需的時間和前期成本，博通的客户將會在大型項目中使用這些芯片。</p>
</div><p>I think both companies should continue to win their fair share of the AI chip market and both will see solid growth. However, I prefer Broadcom's stock a bit more at current levels given the huge opportunity in front of it. Of course in the real world, you should be able to own both over the long run.</p>
<div class="lb-trans"><p>我認為這兩家公司都將繼續贏得其在 AI 芯片市場的合理份額，並且都將看到穩健的增長。然而，考慮到博通面前的巨大機會，我在當前水平上更偏好博通的股票。當然，在現實世界中，您應該能夠長期持有這兩者。</p>
</div>

Better AI Chip Stock: Nvidia vs. Broadcom

- Nvidia 和 Broadcom 在 AI 芯片市場中佔據重要地位。  
- Nvidia 以 GPU 為主導，市場份額超過 80%。  
- Broadcom 則專注於定製 AI 芯片，預計到 2027 財年市場機會達 600 億至 900 億美元。

哪隻 AI 芯片股票更好：英偉達與博通