Verified75% confidenceFactExact time
Anthropic's Responsible Scaling Policy (RSP) stipulates that once a model reaches a specific dangerous capability threshold, it must meet corresponding safety standards before training or deployment can continue.
3
Sources
75%
Confidence
Long-term
Relevance
9/22/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedOpenAI's Responsible Scaling Policy specifies a series of evaluation trigger points, requiring safety evaluations to be completed before training or deployment can continue when a model reaches certain capability thresholds.72% similarUnverifiedThe capability assessment layer systematically evaluates a model's capability level in high-risk domains such as biosecurity, cybersecurity, and autonomous replication before training and deployment.67% similarUnverifiedTechnical safeguards include restrictions on model access permissions, auditing of training data and objective functions, and mechanisms to interrupt training when a model exhibits potentially dangerous capabilities.67% similarUnverifiedDuring the internal development phase, a model may pose three categories of risk: capability spillover, weight security, and training environment interaction.66% similarVerifiedPPO（近端策略优化）以其训练稳定性成为连续控制任务的事实标准，SAC（软演员-评论家）通过最大熵框架在样本效率上具有优势66% similar
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