Core Insights - NVIDIA's CEO Jensen Huang announced multiple open-source models related to physical AI and detailed the performance data of the new chip platform Rubin during a keynote speech at CES [1] - The event attracted significant attention, with a full audience of 3,000 people, indicating strong interest in NVIDIA's advancements in AI technology [1] Group 1: Product Announcements - NVIDIA introduced several open-source models focused on physical AI, marking a shift from solely relying on transistor density improvements to enhancing network processing and low-precision floating-point operations [1] - The Rubin chip platform includes six new chips, such as Vera CPU and Rubin GPU, with Rubin GPU achieving a 50 PFLOPS inference performance, five times that of the previous Blackwell platform [18][20] - The new platform's design allows for a 10-fold reduction in inference token costs and a fourfold decrease in the number of GPUs required for training MoE models compared to Blackwell [20] Group 2: AI Development and Trends - Huang emphasized that AI and computing architecture are undergoing simultaneous transformations, with AI serving as both an application and a new platform [6] - The shift in software development paradigms from coding to model training signifies a complete restructuring of the computing technology stack [6] - The global industry is reallocating R&D budgets towards AI, driven by the modernization of computing infrastructure valued at approximately $10 trillion over the past decade [7] Group 3: Future of AI and Autonomous Vehicles - Huang highlighted that the next phase of AI development involves integrating AI into the physical world, with a focus on teaching AI common sense about physical properties [9] - The transition from non-autonomous to autonomous vehicles is anticipated to occur within the next decade, with a significant portion of cars expected to be fully or highly autonomous [12] - NVIDIA's DRIVE AV software will be implemented in Mercedes-Benz vehicles, with the first autonomous vehicle expected to hit the roads in the U.S. in Q1 2024 [16] Group 4: Collaborations and Industrial Applications - NVIDIA announced a deepened collaboration with Siemens to integrate its physical AI models and Omniverse simulation platform into Siemens' industrial software, covering the entire lifecycle from chip design to production operations [16] - The company is positioned at the forefront of a new industrial revolution, leveraging physical AI to enhance chip design and automation in manufacturing [16] Group 5: Open-Source Models and Global Impact - Huang noted the significant rise of open-source models in the industry, specifically mentioning China's DeepSeek R1 as a model that has surprised the world and activated a global open-source movement [7][8] - The presentation included several open-source models from China, such as Kimi K2 and Qwen, showcasing the competitive advancements in AI technology [8]
直击CES | 黄仁勋新年第一场发布:物理AI的ChatGPT时刻即将到来