SNP-Universal-Embedding

The SNP-Universal-Embedding is the first AI model that mathematically represents human emotional reasoning using a 6-dimensional cognitive space. Unlike traditional embeddings that measure semantic similarity, SNP interprets language through layers of emotion, morality, and intent—enabling machines to reason through contradiction the way humans do. Built on a proprietary Mirror → Prism → Projection architecture, the model converts natural language into six cognitive dimensions: Affective Polarity, Cognitive Dissonance, Moral Alignment, Temporal Reflection, Causal Intention, and Self-Projection. This allows AI systems to understand complex emotional states such as guilt, forgiveness, love, and moral conflict. The system is deployed as a live inference API on Hugging Face, with a front-end demo built in Replit. Users input a Premise and Hypothesis—for example, “She knows he cheats but stays because she still loves him” vs “Love can survive betrayal if it finds purpose in pain.” The model outputs a reasoning score and interpretable vector space reflecting emotional coherence. The SNP model’s purpose is to bring empathy and ethical reasoning to AI. It has potential applications in: Mental-Health AI: detecting emotional dissonance and responding with empathy. Ethical AGI Research: enabling AI to reason about moral contradictions. Conflict-Resolution Systems: quantifying alignment between opposing perspectives. Creative AI: generating emotionally consistent narratives. Key Features: 6-dimensional embedding space for reasoning and emotion Real-time inference via API (~40ms latency) Tested and benchmarked on contradiction and moral reasoning pairs 100% valid output consistency Status: Fully functional and deployed Institution: 366 Degree FitTech & Sci Institute Focus: Emotional AI and Cognitive Modeling for AGI Foundations The SNP-Universal-Embedding project demonstrates that emotion is not a weakness of human cognition—it is its most advanced computation.