黄仁勋Computex讲话：宣布“AI工业革命” ，构建万亿美元AI基建版图

Core Insights - Nvidia is transitioning from a traditional tech company to an "AI infrastructure company," aiming to build a future-oriented ecosystem for computing, robotics, and intelligent systems, with the AI infrastructure market projected to be worth trillions of dollars [1] Group 1: New Product Launches and Collaborations - Nvidia introduced new AI personal computing devices, DGX Spark and DGX Station workstations, and began mass production of the Blackwell RTX Pro6000 motherboard, enabling high-speed GPU cluster systems with 800Gbps communication bandwidth [1] - The company announced a partnership with Foxconn to build a supercomputer equipped with 10,000 Blackwell GPUs, positioning Foxconn as a cloud partner for AI infrastructure [1] Group 2: Development of New Tools and Platforms - Nvidia is developing the Newton physics engine in collaboration with DeepMind and Disney Research, which will be open-sourced in July and support GPU acceleration for training robots in virtual environments [2] - A new GPU-stacked storage platform and AIQ intelligent query system are being created to address the explosion of unstructured data, aiming to disrupt traditional database architectures [2] - The concept of "digital agents" is introduced to tackle the anticipated global workforce shortage of 50 million, providing AI assistants for software development and operations [2] Group 3: Robotics and Mobility - All mobile devices are expected to become robotic, leading to an industrial revolution, with Nvidia working on the Isaac Groot robotic system for autonomous driving and human-machine collaboration [3] - Collaborations with Mercedes and other companies are underway to deploy fleets equipped with end-to-end autonomous driving systems [3] Group 4: Next-Generation Computing - Nvidia is collaborating with Cisco to develop AI systems that integrate quantum technology with 5G/6G, launching the CUDA-Q hybrid computing platform [4] - The company is creating a "light-speed execution" architecture to enhance computing performance, emphasizing the transformative impact of DLSS and neural rendering technologies [4] Group 5: Future Positioning in AI Infrastructure - Data centers are evolving from traditional IT carriers to "AI factories," with a market size projected to reach trillions of dollars, highlighting Nvidia's unique advantage in its algorithm library, particularly the CUDAx ecosystem [5] - The transition from training to inference-driven AI is represented by the full-scale production and deployment of the Grace Blackwell system [5]