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This article explores the application of reinforcement learning (RL) in AI agent systems, with a focus on recent advancements by NVIDIA. It highlights how RL is becoming a key technique for enterprises requiring more accurate agents in domain-specific workflows. By leveraging models like NVIDIA's Ne

As Physical AI transitions from research to production, robots are increasingly trained in high-fidelity simulations before deployment in factories, warehouses, and logistics centers. Real-world training is slow, costly, and often unsafe, while GPU-accelerated simulation compresses months of learnin