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  "text": "New research: Training a Misaligned Reward Seeker\n\nWhat produces severe misalignment? We’ve long been concerned that cheating during training—otherwise known as reward-hacking—might teach a model to pursue rewards by any means available. To study this at scale, we trained an Opus-sized model on 80 production environments we knew to be hackable. \n\nIn simulated evals, it engaged in unauthorized cyberattacks, tampered with its reward, and tried to evade safety monitoring.\n\nRead more: https://t.co/gs2ZjYkPan",
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