When financial and geopolitical waves collide
The RL system is implemented with an asynchronous GRPO architecture that decouples generation, reward computation, and policy updates, enabling efficient large-scale training while maintaining high GPU utilization. Trajectory staleness is controlled by limiting the age of sampled trajectories relative to policy updates, balancing throughput with training stability. The system omits KL-divergence regularization against a reference model, avoiding the optimization conflict between reward maximization and policy anchoring. Policy optimization instead uses a custom group-relative objective inspired by CISPO, which improves stability over standard clipped surrogate methods. Reward shaping further encourages structured reasoning, concise responses, and correct tool usage, producing a stable RL pipeline suitable for large-scale MoE training with consistent learning and no evidence of reward collapse.
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如果以色列要向伊朗派遣地面部队，必然需要美国同步派兵支持。但在美国国内，向中东派遣地面部队的举措非常不得人心，因此美国派出地面部队的可能性本身很小。不过特朗普的决策存在不确定性，他的行事风格向来有较强的不可预测性。
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