昨天晚上，AMD CEO 苏姿丰，又在华尔街掀起了一阵风；她说：到 2030 年，AI 数据中心市场将突破 1 万亿美元。 这句话听起来像在吹牛，但，如果你了解过去 10 年她如何让AMD起死回生，就知道，这个人从来不是说空话的人。 01 首先，为了降低认识门槛，快速过下她是谁？ 很多人知道英伟达的黄仁勋，因为他特别会造梦；但不少人对苏姿丰这个名字有点陌生。她的英文名叫 Lisa Su，是AMD现任的CEO兼董事长。 2014 年，她从一个纯技术背景的工程师，一步步走到这家老牌芯片公司的最高位。 要说履历，她堪称「理工界的女天花板」： 麻省理工学院（MIT）电气工程博士，先后在 IBM 和 Freescale 半导体担任高管；她的专长不是营销、演讲，是让晶体管如何变得更聪明。 接手 AMD 那一年，公司基本快要崩盘，市场份额被英特尔吊打，市值不到 30 亿美元，连员工都在担心明天还有没有班上。 结果不到 10 年，她硬是把 AMD 拉回了牌桌。CPU 端推出的 Ryzen 系列，一口气击穿了 Intel 的防线；GPU 端的 Instinct 系列，对标的正是 NVIDIA。 如果你对这些产品不太熟，也没关系 ...

Core Viewpoint - Nvidia's stock price surge, which once made it the highest-valued company globally, has stagnated as investors become cautious about further investments, recognizing that the adoption of AI computing will not be a straightforward path and will not solely depend on Nvidia's technology [1]. Group 1: Nvidia's Growth Factors and Challenges - Nvidia's most profitable product is the Hopper H100, an enhanced version of its graphics processing unit (GPU), which is set to be replaced by the Blackwell series [3]. - The Blackwell design is reported to be 2.5 times more effective in training AI compared to Hopper, featuring a high number of transistors that cannot be produced as a single unit using traditional methods [4]. - Nvidia has historically invested in the market since its founding in 1993, betting on the capability of its chips to be valuable beyond gaming applications [3][4]. Group 2: Nvidia's Market Position - Nvidia currently controls approximately 90% of the data center GPU market, with competitors like Amazon, Google Cloud, and Microsoft attempting to develop their own chips [7]. - Despite efforts from competitors, such as AMD and Intel, to develop their own chips, these attempts have not significantly weakened Nvidia's dominance [8]. - AMD's new chip is expected to improve sales by 35 times compared to its previous generation, but Nvidia's annual sales in this category exceed $100 billion, highlighting its market strength [12]. Group 3: AI Chip Demand and Future Outlook - Nvidia's CEO has indicated that the company's order volume exceeds its production capacity, with major companies like Microsoft, Amazon, Meta, and Google planning to invest billions in AI and AI-supporting data centers [10]. - Concerns have arisen regarding the sustainability of the AI data center boom, with reports suggesting that Microsoft has canceled some data center capacity leases, raising questions about whether it has overestimated its AI computing needs [10]. - Nvidia's chips are expected to remain crucial even as AI model construction methods evolve, as they require substantial Nvidia GPUs and high-performance networks [12]. Group 4: Competitive Landscape - Intel has struggled to gain traction in the cloud-based AI data center market, with its Falcon Shores chip failing to receive positive feedback from potential customers [13]. - Nvidia's competitive advantage lies not only in hardware performance but also in its CUDA programming language, which allows for efficient programming of GPUs for AI applications [13].