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Beyond VLAs: How World Action Models Reshape Robot Manipulation
A central challenge in robotics is building policies that generalize beyond the demonstrations theyβre trained on. A policy that succeeds in a training scene often fails when object shapes, positions, or lighting change. Generalizing to these new conditions requires the policy to understand the tasks underlying physics, not just mimic the demonstrations. This ability comes from the backbone itβsβ¦
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NVIDIA Technical Blog
- Inside NVIDIA Halos for Robotics: A Full-Stack Functional Safety System for Physical AI
Inside NVIDIA Halos for Robotics: A Full-Stack Functional Safety System for Physical AI
Physical AIβrobots working autonomously alongside people in factories, warehouses, hospitals, and homesβis arriving faster than most expected. Traditional safety which was built for structured environments can not work anymore as the spaces become more unstructured and robots move out of cages. AI-driven safety is the key. Marking a major milestone in the arrival of physical AIβ¦
How to Build In-Vehicle AI Agents with NVIDIA: From Cloud to CarΒ
The automotive cockpit is undergoing a fundamental shift from rule-based interfaces to agentic, multimodal AI systems capable of reasoning, planning, and acting. In most vehicles on the road today, in-vehicle assistants still rely on fixed command-response patterns: interpret a phrase, trigger an action, reset. While effective for well-defined tasks, this approach doesnβt scale to modernβ¦