黄仁勋携Rubin架构亮相CES，英伟达铁了心要做“AI卖铲人”

Core Insights - NVIDIA's CEO Jensen Huang emphasized that artificial intelligence is driving a structural reset across the entire computing industry, positioning NVIDIA as a provider of foundational tools and systems for this transformation [1][3][15] Group 1: AI Market Evolution - Huang reiterated his "platform theory," stating that the computing industry undergoes a fundamental reset every 10 to 15 years, with AI representing a dual-platform migration: the reconstruction of applications and a complete rewrite of the computing stack [3][15] - The global traditional computing system is valued at approximately $10 trillion, which is being systematically modernized for AI computing, with investments coming from corporate R&D budgets, venture capital, and industrial migration [3][15] Group 2: Physical AI - Huang introduced the concept of "Physical AI," aiming to integrate intelligence into the real world, moving beyond digital applications [4][6] - The evolution of AI capabilities is categorized into several stages, culminating in agentic systems that can think and execute tasks in the physical world, addressing the challenges of limited and costly real-world data [6][7] Group 3: Vera Rubin Architecture - The Vera Rubin architecture is a system-level design consisting of six chips, aimed at supporting agentic and physical AI, addressing the limitations of Moore's Law and the exponential growth of model sizes and token generation [8][9] - The architecture features a custom Vera CPU with 88 physical cores and a Rubin GPU that exceeds the performance of its predecessor while maintaining a lower transistor count, emphasizing a new design approach rather than merely increasing scale [11][14] Group 4: System-Level Innovations - The Rubin architecture integrates multiple components to create a cohesive system, allowing for high-density computing and significant performance improvements, including a threefold increase in computational density within a single rack [13][14] - Innovations in energy efficiency and security are highlighted, with the architecture expected to save approximately 6% of energy in global data centers while supporting encrypted computing for secure model deployment [14] Group 5: Competitive Landscape - Huang's presentation aimed to provide a framework for the industry, indicating that AI will permeate every sector and that competition will shift from model parameters to a comprehensive battle for computing power, data, simulation, and system engineering capabilities [15] - NVIDIA's role as a "shovel seller" remains crucial, as it builds platforms and shapes rules while maintaining core engineering capabilities, signaling a shift in the competitive landscape as AI transitions from digital to physical realms [15]