<p>TradingKey - 作为全球人工智能计算能力领域最引人注目的年度盛会，NVIDIA（NVDA）的 GTC 2026 大会将于 3 月 16 日至 19 日举行。</p>
<p>被称为 “人工智能的超级碗”，这一行业盛宴不仅将正式揭示下一代 GPU（如 Rubin 和 “费曼”）的核心技术参数，还将展示计算基础设施的最新技术突破和商业化进展，包括 CPO 交换机、新的电源架构和高效液冷。</p>
<p>NVIDIA 创始人兼首席执行官黄仁勋表示：“GTC 是工业人工智能时代的中心枢纽。人工智能不再是单一的技术突破或应用场景，而是推动各行业发展的不可或缺的基础设施。未来，每家公司都将拥抱人工智能技术，每个国家都将建设人工智能基础设施。从能源供应和芯片制造到数据中心建设、人工智能模型开发和工业应用，人工智能技术栈的每一层都在协同推进，所有这些将在 GTC 大会上全面展示。”</p>
<p>目前，Blackwell Ultra 芯片的大规模生产进展、下一代 “Rubin” 架构的正式发布以及不断演变的地缘政治贸易规则共同为这一全球人工智能计算巨头创造了一个高度复杂的商业环境。</p>
<p>投资者和行业观察者正密切关注此次 GTC 大会的发展，期待看到 NVIDIA 是否能够通过发布突破性的技术成就进一步巩固其在人工智能计算领域的领导地位。</p>
<h2>Vera Rubin 架构的性能革命</h2>
<p>作为 NVIDIA 人工智能技术演进路线图中的核心里程碑，Vera Rubin 架构的正式亮相是一个关键焦点。</p>
<p>与之前的 Blackwell 架构不同，Vera Rubin 将采用 NVIDIA 自主研发的 Vera CPU，取代当前的 Grace CPU，并将配备第六代高带宽内存（HBM4），实现从计算核心到内存架构的全面升级。</p>
<p>根据官方披露的技术参数，旗舰 Vera Rubin 型号 VR200 NVL72 预计将提供 3.3 倍于 Blackwell Ultra GB300 NVL72 的整体推理性能；其 HBM4 内存带宽需求超过 3.0 TB/s，工作速度超过 11 Gbps——这一核心规格比 AMD 的同类产品高出 30%。</p>
<p>与此同时，Rubin 平台引入了五项核心创新技术，包括下一代 NVIDIA NVLink 互连技术、升级版 Transformer 引擎、保密计算模块、RAS 可靠性引擎和自主研发的 NVIDIA Vera CPU。</p>
<p>这些技术突破将带来显著的性能提升。Agentic AI、高级推理和超大规模混合专家（MoE）模型推理的代币成本将降至 NVIDIA Blackwell 平台的十分之一；与此同时，在 MoE 模型训练中，所需的 GPU 数量将仅为上一代的四分之一，显著降低了人工智能的采用门槛，加速其可及性和渗透率。</p>
<p>事实上，NVIDIA 创始人黄仁勋早在 2026 年 1 月 5 日的拉斯维加斯 CES 展会上就透露，Vera Rubin 已进入全面大规模生产。</p>
<p>整个 Rubin 平台由六款全新芯片组成，专门设计用于构建超大规模人工智能超级计算机，其核心目标是帮助企业以最低的总拥有成本构建、部署和安全运行全球最大、最先进的人工智能系统，加速主流人工智能技术在各行业的广泛应用。</p>
<p>黄仁勋当时表示：“当前人工智能训练和推理的计算需求正在呈指数级增长，Rubin 平台的推出时机恰到好处。凭借我们每年迭代一款人工智能超级计算机的研发速度和六款新芯片的协同优化设计，Rubin 平台代表了人工智能技术发展的重要一步。”</p>
<h2>费曼架构：GTC 2026 的隐藏焦点</h2>
<p>除了 Vera Rubin 架构，另一个备受市场关注的悬念话题是 NVIDIA 是否会在此次 GTC 大会上展示原定于 2028 年发布的费曼架构的早期样品静态展示。</p>
<p>NVIDIA 创始人黄仁勋此前暗示，他的主题演讲将展示 “前所未见” 的技术，这一声明使投资者期待一轮新的产品迭代周期和关键供应链选择即将确认，特别是在先进工艺节点和封装形式上的战略权衡。</p>
<p>根据之前的报道，费曼架构将采用台积电（2330）的 A16 1.6nm 工艺技术，并首次引入硅光子技术，使用光信号而非传统电信号来传输数据。</p>
<p>分析公司 Wccftech 认为，如果费曼确实采用台积电 A16 工艺，NVIDIA 将成为这一节点早期大规模生产的首个——也可能是唯一的——客户。这将深度将市场对台积电 A16 产能提升和良率改善的预期与 NVIDIA 的产品节奏联系在一起，进一步增强其在先进工艺领域的影响力。</p>
<p>台积电（TSM）A16 1.6nm 节点被认为是半导体制造的重大飞跃，其核心技术亮点是超级电源轨（SPR）架构，业界称之为 “世界上最小的节点技术。”</p>
<p>Wccftech 指出，NVIDIA 将是 A16 节点初始大规模生产的核心客户，而移动客户可能需要更多时间来适应这一过程标准，因为这需要进行深度架构的改造。这意味着早期 A16 产能的利用和引入节奏将显著围绕 NVIDIA 的产品战略展开。</p>
<p>除了制造工艺的代际飞跃，费曼架构还与另一个潜在线索相关，一些分析认为它可能首次集成 Groq 的 LPU（语言处理单元）硬件堆栈。这些讨论的核心理由是，延迟正成为 AI 计算供应商的关键性能指标之一，特别是在实时推理和对话 AI 等场景中，低延迟能力直接影响用户体验。</p>
<p>市场猜测 NVIDIA 可能采用一种 “混合键合” 技术路径，将 LPU 单元作为封装选项，这种方法与 AMD 的 X3D 处理器相比较。</p>
<p>然而，Wccftech 也指出，这种集成将显著增加芯片设计和生产的难度，这意味着即使技术方向明确，实施的节奏仍可能受到工程复杂性和制造成熟度的限制，从而影响大规模生产的时间表。</p>
<h2>NVIDIA 的关键角色</h2>
<p>当前市场情绪已从过去认为 AI 投资必然会带来回报的信念，转向更加谨慎的态度。投资者对 “先重金投资，等待未来回报” 的长期战略的兴趣下降，关注点转向能够在短期内实现盈利的 AI 商业模式。</p>
<p>自 2025 年下半年以来，海外资本市场弥漫着 AI 焦虑。从 2025 年 10 月底的股价峰值到现在，NVIDIA 的累计跌幅超过 11%，这种波动充分反映了市场的分歧和对 AI 行业前景的担忧。</p>
<p>NVIDIA 创始人黄仁勋曾公开表示，一些人所宣传的 “AI 末日” 言论对全球科技行业产生了负面影响，甚至阻碍了原本打算进入 AI 领域的公司和投资者。</p>
<p>他认为，AI 领域目前正经历一场 “叙事战争”：一方认为 AI 发展的前景黯淡，充满未知的风险和挑战，而另一方则对 AI 的未来持乐观态度，坚信它将推动人类进步。</p>
<p>黄仁勋承认，虽然简单地否定任何一方都是过于绝对的，但那些极度悲观的叙述确实在实质上影响了市场信心和投资决策。</p>
<p>如果 NVIDIA 能够在此次 GTC 大会上交出令人满意的表现，证明其昂贵的计算集群不仅仅是云服务提供商的成本中心，而是能够为企业客户驱动可观收入增长的核心引擎，那么当前的市场波动将成为新一轮稳定增长的转折点。</p>
<p>投资者和行业观察者正密切关注 NVIDIA 的表现，因为这不仅代表了 AI 计算领域的发展方向，还与整个 AI 行业的信心轨迹直接相关。</p>
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2 倍做多英伟达 ETF - Direxion

<p>NVIDIA 的 GTC 2026 大会定于 3 月 16 日至 19 日举行，将揭示下一代 GPU，包括 Vera Rubin 架构，承诺显著的性能提升。Rubin 平台旨在通过降低成本和 GPU 需求来促进 AI 的采用。此外，关于 Feynman 架构的早期样品也有猜测，可能会利用台积电先进的 1.6nm 工艺。黄仁勋强调 AI 在各行业中作为基础设施的重要性，预计大会将展示能够巩固 NVIDIA 在 AI 计算领域领导地位的突破性进展</p>

<p>TradingKey - As the most high-profile annual event in the global AI computing power sector, NVIDIA's ( NVDA) GTC 2026 conference will kick off from March 16 to 19.</p>
<div class="lb-trans"><p>TradingKey - 作为全球人工智能计算能力领域最引人注目的年度盛会，NVIDIA（NVDA）的 GTC 2026 大会将于 3 月 16 日至 19 日举行。</p>
</div><p>Dubbed the &#34;Super Bowl of AI,&#34; this industry feast will not only officially unveil core technical parameters of next-generation GPUs such as Rubin and &#34;Feynman,&#34; but also showcase the latest technological breakthroughs and commercialization progress in computing infrastructure, including CPO switches, new power architectures, and high-efficiency liquid cooling.</p>
<div class="lb-trans"><p>被称为 “人工智能的超级碗”，这一行业盛宴不仅将正式揭示下一代 GPU（如 Rubin 和 “费曼”）的核心技术参数，还将展示计算基础设施的最新技术突破和商业化进展，包括 CPO 交换机、新的电源架构和高效液冷。</p>
</div><p>Jensen Huang, founder and CEO of NVIDIA, stated: &#34;GTC is the central hub of the industrial AI era. AI is no longer a single technological breakthrough or application scenario, but an indispensable infrastructure driving the development of various industries. Future, every company will embrace AI technology, and every nation will build AI infrastructure. From energy supply and chip manufacturing to data center construction, AI model development, and industrial applications, every layer of the AI tech stack is advancing in synergy, all of which will be fully showcased at the GTC conference.&#34;</p>
<div class="lb-trans"><p>NVIDIA 创始人兼首席执行官黄仁勋表示：“GTC 是工业人工智能时代的中心枢纽。人工智能不再是单一的技术突破或应用场景，而是推动各行业发展的不可或缺的基础设施。未来，每家公司都将拥抱人工智能技术，每个国家都将建设人工智能基础设施。从能源供应和芯片制造到数据中心建设、人工智能模型开发和工业应用，人工智能技术栈的每一层都在协同推进，所有这些将在 GTC 大会上全面展示。”</p>
</div><p>Currently, the mass production progress of Blackwell Ultra chips, the official launch of the next-generation &#34;Rubin&#34; architecture, and evolving geopolitical trade rules are collectively creating a highly complex business environment for this global AI computing giant.</p>
<div class="lb-trans"><p>目前，Blackwell Ultra 芯片的大规模生产进展、下一代 “Rubin” 架构的正式发布以及不断演变的地缘政治贸易规则共同为这一全球人工智能计算巨头创造了一个高度复杂的商业环境。</p>
</div><p>Investors and industry observers are closely monitoring the developments of this GTC conference, expecting to see whether NVIDIA can further solidify its leadership in the AI computing sector by releasing breakthrough technological achievements.</p>
<div class="lb-trans"><p>投资者和行业观察者正密切关注此次 GTC 大会的发展，期待看到 NVIDIA 是否能够通过发布突破性的技术成就进一步巩固其在人工智能计算领域的领导地位。</p>
</div><h2>The Performance Revolution of the Vera Rubin Architecture</h2>
<div class="lb-trans"><h2>Vera Rubin 架构的性能革命</h2>
</div><p>As a core milestone in NVIDIA's AI technology evolution roadmap, the official debut of the Vera Rubin architecture is one of the key focuses.</p>
<div class="lb-trans"><p>作为 NVIDIA 人工智能技术演进路线图中的核心里程碑，Vera Rubin 架构的正式亮相是一个关键焦点。</p>
</div><p>Unlike the previous Blackwell architecture, Vera Rubin will feature NVIDIA's proprietary Vera CPU, replacing the current Grace CPU, and will be paired with sixth-generation High Bandwidth Memory (HBM4), achieving a comprehensive upgrade from computing cores to memory architecture.</p>
<div class="lb-trans"><p>与之前的 Blackwell 架构不同，Vera Rubin 将采用 NVIDIA 自主研发的 Vera CPU，取代当前的 Grace CPU，并将配备第六代高带宽内存（HBM4），实现从计算核心到内存架构的全面升级。</p>
</div><p>According to officially disclosed technical parameters, the flagship Vera Rubin model, the VR200 NVL72, is expected to deliver 3.3 times the overall inference performance of the Blackwell Ultra GB300 NVL72; its HBM4 memory bandwidth requirement exceeds 3.0 TB/s with operating speeds reaching over 11 Gbps—a core specification 30% higher than comparable products from AMD.</p>
<div class="lb-trans"><p>根据官方披露的技术参数，旗舰 Vera Rubin 型号 VR200 NVL72 预计将提供 3.3 倍于 Blackwell Ultra GB300 NVL72 的整体推理性能；其 HBM4 内存带宽需求超过 3.0 TB/s，工作速度超过 11 Gbps——这一核心规格比 AMD 的同类产品高出 30%。</p>
</div><p>Meanwhile, the Rubin platform introduces five core innovative technologies, including next-generation NVIDIA NVLink interconnect technology, an upgraded Transformer Engine, confidential computing modules, a RAS reliability engine, and the proprietary NVIDIA Vera CPU.</p>
<div class="lb-trans"><p>与此同时，Rubin 平台引入了五项核心创新技术，包括下一代 NVIDIA NVLink 互连技术、升级版 Transformer 引擎、保密计算模块、RAS 可靠性引擎和自主研发的 NVIDIA Vera CPU。</p>
</div><p>These technological breakthroughs will bring significant performance gains. The token cost for Agentic AI, advanced reasoning, and hyper-scale Mixture-of-Experts (MoE) model inference will drop to one-tenth of that of the NVIDIA Blackwell platform; meanwhile, in MoE model training, the required number of GPUs will be only one-quarter of the previous generation, significantly lowering the barrier to AI adoption and accelerating its accessibility and penetration.</p>
<div class="lb-trans"><p>这些技术突破将带来显著的性能提升。Agentic AI、高级推理和超大规模混合专家（MoE）模型推理的代币成本将降至 NVIDIA Blackwell 平台的十分之一；与此同时，在 MoE 模型训练中，所需的 GPU 数量将仅为上一代的四分之一，显著降低了人工智能的采用门槛，加速其可及性和渗透率。</p>
</div><p>In fact, NVIDIA founder Jensen Huang revealed as early as the CES exhibition in Las Vegas on January 5, 2026, that Vera Rubin had entered full-scale mass production.</p>
<div class="lb-trans"><p>事实上，NVIDIA 创始人黄仁勋早在 2026 年 1 月 5 日的拉斯维加斯 CES 展会上就透露，Vera Rubin 已进入全面大规模生产。</p>
</div><p>The entire Rubin platform consists of six brand-new chips specifically designed for building hyper-scale AI supercomputers, with the core objective of helping enterprises build, deploy, and securely run the world's largest and most advanced AI systems at the lowest total cost of ownership, accelerating the widespread application of mainstream AI technology across industries.</p>
<div class="lb-trans"><p>整个 Rubin 平台由六款全新芯片组成，专门设计用于构建超大规模人工智能超级计算机，其核心目标是帮助企业以最低的总拥有成本构建、部署和安全运行全球最大、最先进的人工智能系统，加速主流人工智能技术在各行业的广泛应用。</p>
</div><p>Huang stated at the time: &#34;The computing demand for current AI training and inference is growing exponentially, and the launch of the Rubin platform is perfectly timed. With our R&amp;D pace of iterating an AI supercomputer every year and the collaborative optimized design of six new chips, the Rubin platform represents a pivotal step forward for the development of AI technology.&#34;</p>
<div class="lb-trans"><p>黄仁勋当时表示：“当前人工智能训练和推理的计算需求正在呈指数级增长，Rubin 平台的推出时机恰到好处。凭借我们每年迭代一款人工智能超级计算机的研发速度和六款新芯片的协同优化设计，Rubin 平台代表了人工智能技术发展的重要一步。”</p>
</div><h2>Feynman Architecture: The Hidden Focus of GTC 2026</h2>
<div class="lb-trans"><h2>费曼架构：GTC 2026 的隐藏焦点</h2>
</div><p>In addition to the Vera Rubin architecture, another suspenseful topic of high market interest is whether NVIDIA will provide a static display of early samples of the Feynman architecture, originally scheduled for release in 2028, at this GTC conference.</p>
<div class="lb-trans"><p>除了 Vera Rubin 架构，另一个备受市场关注的悬念话题是 NVIDIA 是否会在此次 GTC 大会上展示原定于 2028 年发布的费曼架构的早期样品静态展示。</p>
</div><p>NVIDIA founder Jensen Huang previously hinted that his keynote would showcase &#34;never-before-seen&#34; technologies, a statement that has led investors to anticipate that a new round of product iteration cycles and key supply chain choices are about to be confirmed, particularly strategic trade-offs in advanced process nodes and packaging forms.</p>
<div class="lb-trans"><p>NVIDIA 创始人黄仁勋此前暗示，他的主题演讲将展示 “前所未见” 的技术，这一声明使投资者期待一轮新的产品迭代周期和关键供应链选择即将确认，特别是在先进工艺节点和封装形式上的战略权衡。</p>
</div><p>According to previous reports, the Feynman architecture will utilize TSMC's (2330) A16 1.6nm process technology and introduce silicon photonics for the first time, using optical signals instead of traditional electrical signals to transmit data.</p>
<div class="lb-trans"><p>根据之前的报道，费曼架构将采用台积电（2330）的 A16 1.6nm 工艺技术，并首次引入硅光子技术，使用光信号而非传统电信号来传输数据。</p>
</div><p>Analysis firm Wccftech believes that if Feynman does indeed adopt the TSMC A16 process, NVIDIA will become the first—and potentially only—customer for large-scale mass production in the early stages of this node. This would deeply link market expectations for TSMC's A16 capacity ramp-up and yield improvements with NVIDIA's product cadence, further strengthening its influence in the advanced process sector.</p>
<div class="lb-trans"><p>分析公司 Wccftech 认为，如果费曼确实采用台积电 A16 工艺，NVIDIA 将成为这一节点早期大规模生产的首个——也可能是唯一的——客户。这将深度将市场对台积电 A16 产能提升和良率改善的预期与 NVIDIA 的产品节奏联系在一起，进一步增强其在先进工艺领域的影响力。</p>
</div><p>TSMC ( TSM) A16 1.6nm node is considered a major leap in semiconductor manufacturing, with its core technical highlight being the Super Power Rail (SPR) architecture, referred to by the industry as the &#34;world's smallest node technology.&#34;</p>
<div class="lb-trans"><p>台积电（TSM）A16 1.6nm 节点被认为是半导体制造的重大飞跃，其核心技术亮点是超级电源轨（SPR）架构，业界称之为 “世界上最小的节点技术。”</p>
</div><p>Wccftech points out that NVIDIA will be the core customer for the initial mass production of the A16 node, whereas mobile customers may require more time to adapt to this process standard due to the need for deep architectural overhauls. This means that the utilization and introduction pace of early A16 capacity will revolve significantly around NVIDIA's product strategy.</p>
<div class="lb-trans"><p>Wccftech 指出，NVIDIA 将是 A16 节点初始大规模生产的核心客户，而移动客户可能需要更多时间来适应这一过程标准，因为这需要进行深度架构的改造。这意味着早期 A16 产能的利用和引入节奏将显著围绕 NVIDIA 的产品战略展开。</p>
</div><p>Beyond the generational leap in manufacturing processes, the Feynman architecture is also linked to another potential clue, with some analysis speculating it might integrate Groq's LPU (Language Processing Unit) hardware stack for the first time. The core rationale behind these discussions is that latency is becoming one of the key performance metrics for AI computing vendors, particularly in scenarios such as real-time inference and conversational AI, where low-latency capabilities directly impact user experience.</p>
<div class="lb-trans"><p>除了制造工艺的代际飞跃，费曼架构还与另一个潜在线索相关，一些分析认为它可能首次集成 Groq 的 LPU（语言处理单元）硬件堆栈。这些讨论的核心理由是，延迟正成为 AI 计算供应商的关键性能指标之一，特别是在实时推理和对话 AI 等场景中，低延迟能力直接影响用户体验。</p>
</div><p>Market speculation suggests that NVIDIA might adopt a &#34;hybrid bonding&#34; technology path, incorporating LPU units as an on-package option, a method compared to AMD's X3D processors.</p>
<div class="lb-trans"><p>市场猜测 NVIDIA 可能采用一种 “混合键合” 技术路径，将 LPU 单元作为封装选项，这种方法与 AMD 的 X3D 处理器相比较。</p>
</div><p>However, Wccftech also noted that such integration would significantly increase chip design and production difficulty, meaning that even if the technical direction is clear, the implementation pace could still be constrained by engineering complexity and manufacturing maturity, thereby affecting the mass production timeline.</p>
<div class="lb-trans"><p>然而，Wccftech 也指出，这种集成将显著增加芯片设计和生产的难度，这意味着即使技术方向明确，实施的节奏仍可能受到工程复杂性和制造成熟度的限制，从而影响大规模生产的时间表。</p>
</div><h2>NVIDIA's Key Role</h2>
<div class="lb-trans"><h2>NVIDIA 的关键角色</h2>
</div><p>Current market sentiment has shifted significantly from the past belief that AI investment would inevitably yield returns toward a more cautious stance. Investor interest in the long-term strategy of &#34;investing heavily first and waiting for future returns&#34; has declined, with focus turning toward AI business models capable of achieving profitability in the near term.</p>
<div class="lb-trans"><p>当前市场情绪已从过去认为 AI 投资必然会带来回报的信念，转向更加谨慎的态度。投资者对 “先重金投资，等待未来回报” 的长期战略的兴趣下降，关注点转向能够在短期内实现盈利的 AI 商业模式。</p>
</div><p>Since the second half of 2025, a cloud of AI anxiety has lingered over overseas capital markets. From its stock price peak in late October 2025 to the present, NVIDIA has seen a cumulative decline of over 11%, a volatility that fully reflects market divergence and concerns regarding the prospects of the AI industry.</p>
<div class="lb-trans"><p>自 2025 年下半年以来，海外资本市场弥漫着 AI 焦虑。从 2025 年 10 月底的股价峰值到现在，NVIDIA 的累计跌幅超过 11%，这种波动充分反映了市场的分歧和对 AI 行业前景的担忧。</p>
</div><p>NVIDIA founder Jensen Huang has previously stated publicly that the &#34;AI doomsday&#34; rhetoric promoted by some is negatively impacting the global tech industry, even deterring companies and investors who originally intended to enter the AI space.</p>
<div class="lb-trans"><p>NVIDIA 创始人黄仁勋曾公开表示，一些人所宣传的 “AI 末日” 言论对全球科技行业产生了负面影响，甚至阻碍了原本打算进入 AI 领域的公司和投资者。</p>
</div><p>He believes the AI field is currently undergoing a &#34;war of narratives&#34;: one side views the prospects of AI development as bleak and filled with unknown risks and challenges, while the other remains optimistic about the future of AI, firmly believing it will drive human progress.</p>
<div class="lb-trans"><p>他认为，AI 领域目前正经历一场 “叙事战争”：一方认为 AI 发展的前景黯淡，充满未知的风险和挑战，而另一方则对 AI 的未来持乐观态度，坚信它将推动人类进步。</p>
</div><p>Huang admitted that while simply dismissing either side would be too absolute, those extremely pessimistic narratives are tangibly affecting market confidence and investment decisions.</p>
<div class="lb-trans"><p>黄仁勋承认，虽然简单地否定任何一方都是过于绝对的，但那些极度悲观的叙述确实在实质上影响了市场信心和投资决策。</p>
</div><p>If NVIDIA can deliver a satisfactory performance at this GTC conference, proving that its expensive computing clusters are not just cost centers for cloud service providers but core engines capable of driving substantial revenue growth for enterprise customers, then the current market volatility will serve as a turning point for a new round of steady growth.</p>
<div class="lb-trans"><p>如果 NVIDIA 能够在此次 GTC 大会上交出令人满意的表现，证明其昂贵的计算集群不仅仅是云服务提供商的成本中心，而是能够为企业客户驱动可观收入增长的核心引擎，那么当前的市场波动将成为新一轮稳定增长的转折点。</p>
</div><p>Investors and industry observers are closely monitoring NVIDIA's performance, as it not only represents the developmental direction of the AI computing sector but is also directly linked to the confidence trajectory of the entire AI industry.</p>
<div class="lb-trans"><p>投资者和行业观察者正密切关注 NVIDIA 的表现，因为这不仅代表了 AI 计算领域的发展方向，还与整个 AI 行业的信心轨迹直接相关。</p>
</div><p>Find out more</p>
<div class="lb-trans"><p>了解更多</p>
</div>

Nvidia GTC 2026 Preview: Two Major Architectures Launch Together, Can They Solve the AI Anxiety Dilemma?

- NVIDIA 将于 3 月 16 至 19 日举办 GTC 2026 大会，展出新一代 GPU 和技术进展。  
- CEO 黄仁勋表示，AI 是各行业发展的基础设施，未来各公司和国家将拥抱 AI 技术。  
- 投资者关注 NVIDIA 的技术突破及市场表现，期望其将巩固在 AI 计算领域的领导地位。

英伟达 GTC 2026 预览：两大架构同时发布，它们能否解决 AI 焦虑的困境？