Today we're releasing @nvidia AlpaGym, our new open-source reinforcement learning (RL) framework for end-to-end autonomous driving. A key challenge for #Physical# #AI# is enabling policies to learn from the consequences of their actions. While supervised learning can teach a model to imitate behavior, robust autonomy ultimately requires learning through interaction with the environment. AlpaGym enables exactly that. Built on top of: - AlpaSim: our high-fidelity closed-loop autonomous driving simulator - Cosmos-RL: NVIDIA's distributed RL training and rollout infrastructure AlpaGym provides the glue that connects simulation, training, and driving policies into a scalable framework for post-training autonomous vehicle models in closed loop. With AlpaGym, researchers and developers can: ✅ Train end-to-end driving policies using reinforcement learning ✅ Run large-scale closed-loop simulations ✅ Experiment with new reward functions, policy architectures, and training strategies ✅ Benchmark models on public leaderboards 📖 Learn how it works: 💻 GitHub: 🏆 Open Challenges: - AlpaSim Closed-Loop E2E Driving Challenge: - Physical AI AV Reasoning Challenge: Learn more about the #Alpamayo# open platform: #PhysicalAI# #AutonomousDriving# #ReinforcementLearning# #Robotics# #OpenSource# #NVIDIA# #MachineLearning# @NVIDIADRIVE @NVIDIAAI