ended5월 20일· 1 sources
Designing Moral Friction: Why the Future of AI Alignment is Curved
AI 정렬의 새로운 패러다임, DRM Transformer가 제안하는 ‘곡선형 공간’의 미학
Why it matters
Current alignment methods rely on external behavioral layers like RLHF, but the DRM Transformer proposes embedding safety directly into the model's underlying geometry. By introducing 'costly paths' and semantic anchors within a curved manifold, this approach shifts AI safety from post-hoc filtering to an intrinsic architectural property.
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DRM TransformerGeodesic AttentionAI AlignmentLatent ManifoldGeometric Alignment