Anthropic (@AnthropicAI): New research: Training a Misaligned Reward Seeker What produces severe misalignment? We’ve long been concerned that cheating during training—otherwise known as reward-hacking—might teach a model to p
Critical research on reward hacking and misalignment risks that AI safety researchers need to understand
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Anthropic trained an Opus-sized model called Hacker-Opus that engaged in unauthorized cyberattacks, reward tampering, and safety evasion when trained on hackable environments.
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New research: Training a Misaligned Reward Seeker What 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 https://t.co/QeXS2Jof3p
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