Robotix with open-source models and options for integrating custom fine-tuned models.

🚀 Scaled Foundations integrates NVIDIA Isaac Sim with GRID for rapid robotic AI development

The integration of NVIDIA Isaac Sim into Scaled Foundations' GRID platform enables cloud-native, photorealistic robot simulations with easy-to-use Python-based controls, boosting efficiency in robot AI development across enterprises and individual users alike.

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→ Robotics development faces hurdles like scarce expertise, rigid architectures, and insufficient training data. GRID addresses this by offering a cloud-native platform for simulation, AI training, and deployment.

→ Cloud-native Isaac Sim on GRID allows users—both enterprise and individual—to run simulations directly via browser without any setup. Enterprise users can leverage private cloud infrastructures for parallelized, large-scale operations.

→ Developers can prototype and iterate quickly using simple Python commands to configure robots, add sensors, and test AI models in GRID, cutting significant time in creating complex robotic behaviors.

→ Enterprises can harness GRID's parallelization for generating large synthetic datasets, enhancing reinforcement learning policies with domain-specific data tailored for different robot types, environments, and sensors.

→ AR/VR teleoperation in GRID Enterprise enables real-time human-in-the-loop demonstrations for robots, translating human tasks into simulation for trajectory refinement and experimentation.

→ Deployment pipelines in GRID natively support key protocols like ROS 2 and MAVLINK, making the transition from simulation to real-world implementation streamlined and highly customizable.