How to Post-Train Autonomous Vehicle Models in Closed-Loop with NVIDIA Alpamayo
Developing autonomous vehicle (AV) policies requires bridging an important gap between training and deployment. Vision-language-action (VLA) models that can...
Developing autonomous vehicle (AV) policies requires bridging an important gap between training and deployment. Vision-language-action (VLA) models that can reason over more complex driving scenes and produce richer intermediate reasoning are predominantly trained in open-loop, where model outputs are directly compared to ground-truth behaviors without considering their effect on the environment.
Physical AI systems must understand the real world before they can act within it. Robots, autonomous vehicles, and smart spaces need to understand what's...
Each wave of AI has created a new scaling law. Pretraining scaled intelligence through larger datasets, more parameters, and massively parallel GPU systems....