Nvidia(US:NVDA) 具身智能之心·2025-08-26 04:45Core Viewpoint - NVIDIA has launched the Jetson Thor, a new robotic computing platform that significantly enhances AI computing power and efficiency, marking a leap towards the era of physical AI and general robotics [1][6][22]. Group 1: Product Features - Jetson Thor boasts an AI computing power of 2070 TFLOPS, which is 7.5 times higher than its predecessor, Jetson Orin, while achieving a 3.5 times improvement in energy efficiency [1][5]. - The platform includes 128GB of memory, an unprecedented configuration for edge computing devices [2]. - It supports multiple AI models simultaneously on edge devices, enhancing the capabilities of robots to interact with and even change the physical world [5][6]. Group 2: Technical Specifications - The GPU is based on the Blackwell architecture, featuring up to 2560 CUDA cores and 9 fifth-generation Tensor Cores, with support for Multi-Instance GPU (MIG) technology [16]. - The CPU consists of a 14-core Arm Neoverse V3AE, designed for real-time control and task management, with significant performance improvements over previous generations [16]. - Storage and bandwidth are upgraded to 128GB 256-bit LPDDR5X with a memory bandwidth of 273GB/s, supporting large Transformer inference and high-concurrency video encoding [16]. Group 3: Market Adoption - A significant number of Chinese companies, including Union Medical, Wanji Technology, and UBTECH, are among the first to adopt the Jetson Thor platform [19]. - Boston Dynamics is integrating Jetson Thor into its Atlas humanoid robot, enabling it to utilize computing power previously only available in servers [20]. - Agility Robotics plans to use Jetson Thor as the core computing unit for its sixth-generation Digit robot, aimed at logistics tasks in warehouses and manufacturing environments [21]. Group 4: Development and Simulation - NVIDIA emphasizes the importance of a three-computer system for achieving physical AI: a DGX system for training AI, an Omniverse platform for simulation, and the Jetson Thor as the robot's "brain" [22]. - Continuous training, simulation, and deployment cycles are essential for upgrading the robot's capabilities even after deployment [24].