Unverified50% confidenceFactExact time
OpenAI calls the security protection of training and evaluation environments "containment", with the goal of restricting training and evaluation activities within controllable boundaries so that the impact of a single point of failure does not spill over.
1
Sources
50%
Confidence
Long-term
Relevance
10/23/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedTraining-free safety guidance refers to the general category of safety protection methods that do not modify diffusion model weights and only intervene in the generation process during the inference sampling stage.74% similarUnverifiedOpenAI has extended multistage monitoring to three sensitive areas: high-risk training, evaluation, and tool-call inference.72% similarUnverifiedOpenAI'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.71% similarUnverifiedRepresentative works in training-free safety protection include Safe Latent Diffusion (SLD), Erasing Concepts (ESD), and guidance-based suppression methods.69% 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.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1091447API
curl https://kongchang.com/api/v1/knowledge/claims/1091447MCP
get_claim(id=1091447)