3 6 Ke·2025-08-28 07:02Core Insights - Huang Renxun has launched the Jetson T5000, a powerful edge computing platform with a computing power of 2070 TFLOPS, specifically designed for humanoid robots [1][2] - This advancement allows humanoid robots to perform more AI inference calculations and real-time processing of multimodal sensor data locally, without relying on cloud computing [2][4] - The development of humanoid robots has gained significant attention from tech leaders like Elon Musk and Huang Renxun, elevating the status of humanoid robots in the tech industry [4][6] Industry Trends - The Jetson series has evolved significantly since its inception, with the first model, Jetson TK1, launched in 2014, now reaching up to 2070 TFLOPS with the latest Jetson AGX Thor [8][10] - Major companies like JD.com and Meituan have utilized the Jetson AGX Xavier for their logistics robots, showcasing the practical applications of this technology in the industry [8] - Huang Renxun's focus on robotics and AI has positioned NVIDIA as a leader in the field, with the Jetson platform being a cornerstone of this strategy [6][12] Technological Developments - Current humanoid robots typically require 100-200 TFLOPS of computing power, which is sufficient for basic tasks like grasping and sorting [14][16] - For more complex tasks involving multi-sensor data processing, higher computing power is necessary, leading to the exploration of smaller models to optimize performance [16][19] - Boston Dynamics' Atlas robot has successfully implemented a small model with 450 million parameters, demonstrating that smaller models can effectively reduce computational load while enhancing real-time data processing capabilities [19][21] Future Directions - The industry is moving towards the use of smaller models for specific tasks, as opposed to relying on large models for all operations, which can be inefficient [21][23] - This approach aligns with the ongoing trend of optimizing hardware resources and task execution in humanoid robots, indicating a potential pathway for future advancements in the field [23]