人形机器人，需要多少算力？

Core Viewpoint - The article discusses the advancements in humanoid robots, particularly focusing on the significant increase in edge computing power provided by NVIDIA's Jetson T5000, which boasts a computing power of 2070 TFLOPS, enabling more efficient AI inference and real-time processing of multimodal sensor data [6][10][15]. Group 1: Technological Advancements - NVIDIA's Jetson series has evolved from the initial Jetson TK1 with less than 1 TFLOPS to the current Jetson AGX Thor with 2070 TFLOPS, marking a significant leap in computational capabilities for robotics [11][13]. - The Orin series, with 100 TFLOPS, has become a foundational AI computing platform for many humanoid robots in China, showcasing the growing importance of computational power in the robotics sector [15][19]. Group 2: Industry Leaders and Their Impact - Elon Musk and Jensen Huang are highlighted as key figures in the resurgence of humanoid robots, with Musk's announcement of entering the humanoid robot space and Huang's continuous enhancement of computing platforms [7][10]. - Huang's vision for NVIDIA extends beyond traditional AI into the realm of "Physical AI," indicating a broader ambition for the company's role in robotics [15][19]. Group 3: Current Capabilities and Future Directions - Most humanoid robots currently utilize edge computing power in the range of 100-200 TFLOPS, which is sufficient for basic tasks like grasping and sorting [17][19]. - The article suggests a shift towards smaller models for AI processing, as demonstrated by Boston Dynamics' Atlas robot, which uses a 450 million parameter model to efficiently handle tasks while reducing computational load [21][22].