Core Viewpoint - Nvidia's new Blackwell Ultra and Rubin chips are set to lead the next wave of AI investment, focusing on both generative and inferential AI, with significant improvements in memory bandwidth and processing capabilities [1][3][11]. Summary by Sections Blackwell Ultra and Rubin Chips - The Blackwell Ultra chips, set to be released in 2024, feature a memory bandwidth increase from 192GB to 288GB, enabling the handling of larger AI models and more efficient processing of intensive workloads [1]. - The Rubin chips, expected in 2026, will replace Blackwell and consist of a custom Arm CPU named Vera, designed for parallel processing, allowing for a modular design that accommodates multiple chip types for specific workloads [2]. Performance Enhancements - Rubin is projected to achieve AI inference speeds of 50 petaflops, approximately 2.5 times faster than Blackwell, with plans for a combined Rubin GPU to reach 100 petaflops and 1 terabyte of onboard memory by 2027 [3]. - The Blackwell Ultra and Rubin chips are designed to enhance inference capabilities, addressing the growing demand for complex, dynamic AI models that require real-time adjustments [3][4]. Market Position and Competition - Nvidia currently dominates the AI accelerator market, supporting about 90% of data center workloads, which solidifies its high valuation and status as one of the world's most valuable companies [5]. - The Blackwell Ultra system claims to provide 11 times faster AI inference speed and 7 times higher throughput compared to the previous generation, indicating a strong competitive edge [5]. Industry Dynamics - Competitors like Google and Amazon are developing their own chips tailored to their ecosystems, not necessarily to compete directly with Nvidia but to optimize their resource utilization [7]. - AMD is making strides with its Instinct MI300X chip, which is being integrated into data centers by companies like Microsoft and Meta, indicating a growing competitive landscape [7][8]. Future Outlook - Nvidia's new chips are expected to open up new applications for AI, transitioning the company from a hardware manufacturer to a critical interface between hardware and software [6]. - Despite the emergence of competitors, Nvidia's software ecosystem, including CUDA, remains a significant barrier for rivals, as replicating this infrastructure is a daunting task [9]. Investment Sentiment - Analysts predict that the AI data center market could reach trillions of dollars, with Nvidia positioned at the center of this growth, supported by high gross margins of approximately 73-75% [13]. - The recent stock price decline of Nvidia is viewed as irrational, with the current market conditions presenting a potential buying opportunity for investors [13][14].
英伟达的新款 Blackwell Ultra 和 Rubin 芯片如何引领下一波 AI 浪潮