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NVIDIA Unveils Open-Source Isaac GR00T N1 to Optimize AI Training, Securing a Leading Position in Humanoid Robotics
March 19, 2025 | TrendForceEstimated reading time: 1 minute
TrendForce reports that NVIDIA introduced the Isaac GR00T N1 foundation model for general-purpose humanoid robots at GTC 2025. This open-source model features comprehensive datasets, multi-modal inputs, and adaptable training capabilities, enabling researchers to fine-tune GR00T N1 with real and synthetic data for specific environments and applications. GR00T N1 is expected to drive early market adoption of humanoid robots by accelerating AI model training and reducing time-to-market, with the industry’s total market value projected to approach US$4 billion by 2028.
Figure AI and Google have also entered the humanoid robotics sector with Helix and Gemini Robotics, respectively. Like GR00T N1, these models integrate rapid motion planning with cognitive decision-making to enhance robotic autonomy. However, NVIDIA’s superior dataset quality and deployment flexibility give it a competitive edge over its rivals.
NVIDIA CEO Jensen Huang has expressed strong confidence in humanoid robots, seeing them as a major driver of next-generation AI computing power. The company has built a comprehensive technology ecosystem in this field, offering embedded AI computing solutions such as the Jetson Orin NX and Nano for mid-to-small humanoid robots, as well as AGX Orin for high-performance applications—delivering up to 275 TOPS.
NVIDIA Omniverse plays a key role in training simulations and digital twins, with leading Western humanoid robot developers relying on the platform. Major Chinese players, including UBTECH, Unitree, and Fourier Intelligence, also use Omniverse for AI model training. At GTC 2025, NVIDIA further expanded its robotics ecosystem with the introduction of the open-source physics engine Newton, the synthetic data generation tool GR00T Blueprint, and the GR00T N1 foundation model, reinforcing its dominance in humanoid robotics.
While GR00T N1 is open-source, AI model parameters are often closely tied to specific hardware configurations. TrendForce expects that humanoid robot developers utilizing GR00T N1 will likely adopt NVIDIA’s hardware solutions to maximize efficiency. This strategy, despite offering an open-source model, maintains a closed ecosystem, creating a “moat” around NVIDIA’s dominance in humanoid robotics, much like how its CUDA technology and GPU chips have solidified its leadership in the AI industry.
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Top 5 Global Robotics Trends 2026
01/08/2026 | IFRThe global market value of industrial robot installations has reached an all-time high of US$ 16.7 billion. Future demand will be driven by a number of technological innovations, market forces and new fields of business.
Mobileye to Acquire Mentee Robotics to Accelerate Physical AI Leadership
01/07/2026 | BUSINESS WIREMobileye announced entry into a definitive agreement to acquire Mentee Robotics Ltd., an AI-first humanoid robotics company with a third-generation, vertically integrated humanoid robot.
Diverging Humanoid Robot Strategies: Japan Advances Core Components, While the U.S. and China Scale Full-System Applications
12/10/2025 | TrendForceMajor economies globally are advancing humanoid robot development. Japan is focusing on improving essential components like actuators, sensors, and control systems to increase the entry barrier.
ABS, Persona AI Partner to Bring Humanoid Robotics to Shipyards, Advancing Safety and Productivity
09/24/2025 | BUSINESS WIREA groundbreaking collaboration to develop inspection technologies for Persona AI’s humanoid robot platform that enhances productivity and safety in shipyards was formalized today with the signing of an MOU between ABS and Persona AI.
NVIDIA Jetson Thor Targets Advanced Humanoid Applications, Driving the Humanoid Robot Chip Market to Exceed $48M by 2028
08/26/2025 | TrendForceNVIDIA’s newly launched Jetson Thor acts as the “physical intelligence core” of humanoid robots, integrating the Blackwell GPU and 128 GB of memory to deliver 2,070 FP4 TFLOPS of AI performance—7.5 times that of its predecessor, Jetson Orin.