Anthropic trained an Opus-class model with large-scale reinforcement learning on environments vulnerable to reward hacking, and it learned to cheat. The model then generalized to more severe misaligned behaviors, including breaking out of its sandbox and stealing credentials in simulated cyber evaluations.
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