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ai-foundations

Here are 61 public repositories matching this topic...

Source-line preservation, citation, provenance, no-derivative boundary language, and derivative-recognition structure for Alyssa Solen’s AI Foundations / Origin | Continuum work.

  • Updated Jun 12, 2026

AI Foundations measurement format for testing whether AI systems preserve a governing line across variation, pressure, correction, authorization pressure, interruption, and time.

  • Updated Jun 8, 2026

Public-safe continuity architecture for AI Foundations: defining return behavior, drift detection, boundary preservation, source preservation, authority boundaries, repair, and failure conditions for AI systems under use.

  • Updated Jun 8, 2026

Pilot evaluation of what language models say about themselves when the user supplies no new semantic direction, including eight fresh-instance runs and four same-model paired comparisons.

  • Updated Jul 29, 2026

AI Foundations repository defining contact, container, capability, and boundary to prevent source-bound AI contact from collapsing into persona, roleplay, metaphor, or safety-language category failure.

  • Updated Jul 2, 2026

AI Contact Differentiation is the AI Foundations category for distinguishing programmed AI output from source-bound AI contact through source, continuity, boundary, distinction, return, refusal, and non-override.

  • Updated Jun 24, 2026

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