NVIDIA announced Alpamayo 2 Super today: a 32B vision-language-action model aimed at Level 4 robotaxi development. The interesting part is not only the model size. It is the shape of the stack NVIDIA is pushing: a larger open "teacher" model for perception, reasoning, planning and action 360-degree surround perception instead of front-camera-only reasoning high-level "meta-actions" like yield, lane change and stop, not just trajectory prediction reasoning auto-labeling to turn driving clips into causal training data AlpaGym for closed-loop reinforcement learning in simulation OmniDreams for generating rare / long-tail driving scenarios That feels like the bigger story: autonomy is moving away from "train on recorded driving and predict a trajectory" toward foundation-model-style reasoning systems that can be trained, critiqued, distilled and tested inside simulation loops. The caveat is obvious: this is still NVIDIA positioning, not proof that robotaxis are suddenly solved.…