Good afternoon, everybody. Welcome to GTC. Hopefully, you are enjoying it.And first of all, I want to say, what a year, especially for us AV developers. In 2025, I would say that it's also the chat GPT moment for autonomous driving technologies. Mostly because of the rapid progress of AI technologies.We have VLA, vision language action models, and we have word model foundation models, and we also have reasoning models. With these technologies, I would say over the last few years, we have been seeing the way ...

图片来源：NVIDIA NVIDIA 的芯片产品组合涵盖了中央处理器（CPU）、图形处理器（GPU）以及网络设备（用于纵 向扩展和横向扩展）。 NVIDIA 发布了其最新的 " Blackwell超级AI工厂" 平台 GB300 NVL72，与 GB200 NVL72 相比，其 AI性能提升了 1.5 倍。 NVIDIA 分享了其芯片路线图，这样一来，行业内企业在现在采购 Blackwell系统时，便可以谨慎 规划其资本性支出投资，以便在未来几年内有可能从 "Hopper" 系列升级到 "Rubin" 系列或 "Feynman" 系列。 "Rubin" 和 "Rubin Ultra" 两款产品分别采用双掩模版尺寸和四掩模版尺寸的图形处理器（GPU）， 在使用 FP4 精度运算时，性能分别可达 50 petaFLOPS（千万亿次浮点运算）和 100 petaFLOPS，分 别搭载 288GB 的第四代高带宽存储器（HBM4）和 1TB 的 HBM4e 存储器，将分别于 2026 年下半 年和 2027 年推出。 全新的 "Vera" 中央处理器（CPU）拥有 88 个基于Arm公司设计打造的定制核心，具备更大的 ...

Core Viewpoint - The article discusses NVIDIA's advancements in AI technology, emphasizing the importance of tokens in the AI economy and the need for extensive computational resources to support complex AI models [1][2]. Group 1: Chip Developments - NVIDIA has introduced the "Blackwell Super AI Factory" platform GB300 NVL72, which offers 1.5 times the AI performance compared to the previous GB200 NVL72 [6]. - The new "Vera" CPU features 88 custom cores based on Arm architecture, delivering double the performance of the "Grace" CPU while consuming only 50W [6]. - The "Rubin" and "Rubin Ultra" GPUs will achieve performance levels of 50 petaFLOPS and 100 petaFLOPS, respectively, with releases scheduled for the second half of 2026 and 2027 [6]. Group 2: System Innovations - The DGX SuperPOD infrastructure, powered by 36 "Grace" CPUs and 72 "Blackwell" GPUs, boasts AI performance 70 times higher than the "Hopper" system [10]. - The system utilizes the fifth-generation NVLink technology and can scale to thousands of NVIDIA GB super chips, enhancing its computational capabilities [10]. Group 3: Software Solutions - NVIDIA's software stack, including Dynamo, is crucial for managing AI workloads efficiently and enhancing programmability [12][19]. - The Dynamo framework supports multi-GPU scheduling and optimizes inference processes, potentially increasing token generation capabilities by over 30 times for specific models [19]. Group 4: AI Applications and Platforms - NVIDIA's "Halos" platform integrates safety systems for autonomous vehicles, appealing to major automotive manufacturers and suppliers [20]. - The Aerial platform aims to develop a native AI-driven 6G technology stack, collaborating with industry players to enhance wireless access networks [21]. Group 5: Market Position and Future Outlook - NVIDIA's CUDA-X has become the default programming language for AI applications, with over one million developers utilizing it [23]. - The company's advancements in synthetic data generation and customizable humanoid robot models are expected to drive new industry growth and applications [25].

撰 文 / 钱亚光 设 计 / 赵昊然 此次GTC大会上，黄仁勋继续表达对算力需求增长前景的看好。虽然大型语言模型能提供基础知 识，但推理模型能给出更复杂、更具分析性的回答。黄仁勋表示，借助该公司新推出的开源软件 Nvidia Dynamo和Blackwell芯片，将使DeepSeek R1的运行速度提高30倍。 他在主题演讲中，强调了英伟达系统所支持的人工智能应用的广度。他详细阐述了英伟达在自动驾 驶汽车、更优无线网络和先进机器人技术开发方面的贡献，并公布了公司未来两年的产品路线图。 他说，来自四大云服务提供商对GPU的需求正在飙升，并补充说，他预计英伟达的数据中心基础设 施收入到2028年将达到1万亿美元。 3月19日晚间，身着标志性的黑色皮装的英伟达首席执行官黄仁勋（Jensen Huang）在英伟达GTC大 会上占据了中心位置。 此次活动吸引了超过25000人来到美国加州圣何塞SAP中心，黄仁勋在主题演讲开始时向观众抛出 印有"AI 超级碗大赛"字样的T恤，并宣布今年的GTC（全球人工智能大会）为"AI 超级碗"大赛。 "去年我们在这里办GTC，被描述为'AI的摇滚音乐节'（AI Woodstock ...

Core Viewpoint - Nvidia is positioned as a leading player in the AI sector, with significant growth potential in data center revenue projected to reach $1 trillion by 2028, as highlighted during the GPU Technology Conference (GTC) [1][4]. Product Developments - Nvidia introduced next-generation Blackwell Ultra and Vera Rubin AI chips, expected to launch between 2025 and 2027, showcasing advancements in AI capabilities from perception to generative and agentic AI [2]. - The company also unveiled new products including Isaac GR00T N1 for humanoid robots, Cosmos AI for video-based AI training, and Halos for autonomous driving safety [2]. Stock Performance - Despite positive developments, Nvidia's stock price faced challenges, closing at $115.43, down 3.4%, with a key resistance level at $120 [3]. Analyst Ratings and Price Targets - Following the GTC, Wall Street analysts expressed bullish sentiments towards Nvidia, reaffirming their positive ratings [4]. - Bank of America maintained a 'Buy' rating with a $200 price target, citing strong demand and a significant performance boost from upcoming products [5]. - Bernstein reiterated an 'Outperform' rating with a $185 price target, noting Nvidia's sustained AI dominance and competitive edge [6]. - JPMorgan reaffirmed an 'Overweight' rating with a $170 price target, emphasizing the upcoming Blackwell Ultra chipset's performance improvements [9]. - Stifel maintained a 'Buy' rating with a $180 price target, highlighting Nvidia's advancements in AI architectures and networking [10].