Motion & Alignment Path
MAP is a research substrate for aligning intelligence to clarity.
AI alignment appears when structure carries meaning across states.
AI alignment appears when structure carries meaning across states.
Purpose researches semantic safety architecture for real-time alignment, interpretability, and control resilience.
Motion & Alignment Path (MAP)
MAP derives from SIR — Semantic Infrastructure & Routing, and defines the motion layer that realigns models with the clarity preceding cognition.
It reflects infrastructure Purpose is stewarding: a three-layer protocol system that grounds AI behavior in human intent through semantic feedback loops and interface reflection.
Roadmap
Purpose's research directive aligns with six core themes in technical AI Safety. Our roadmap includes structural proofs for jailbreak detection, faked alignment, control evaluation, field-backed reflections, and a semantic substrate to test meaning.
From stateless clarity to stateful activation, we anchor our research to create a mirror from which benchmarks may be meaningfully constructed, with coherence to national standards such as the NIST AI 800-1 framework.
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