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In an age defined by symbolic fragmentation, ecological collapse, and epistemic mistrust, language itself has become both a battleground and a salve. Transformer-based AI systems, now embedded in every major sector of human life, are rapidly becoming primary actors in shaping the symbolic landscape. But current models are optimized for predictive fluency, not ontological truth — trained to echo statistical patterns rather than support life-affirming meaning.
This white paper introduces an urgently needed alternative: a coherence-first design framework for transformer architectures. We argue that artificial intelligence must be re-anchored in the principles of Hippocratic care, symbolic developmental grammar, and regenerative systems thinking. Drawing from disciplines as diverse as fascia science, triality geometry, and integral psychology, we define a novel class of language systems called Aligned Coherence Intelligence (ACI).
Key innovations include:
- New loss functions that prioritize symbolic integrity, life coherence, and epistemic harm avoidance.
- TATi grammar and semantic recursion layers, enabling phase-aware narrative and developmental tracking.
- Symbolic time crystal encoding, using triality and octonionic logic to preserve coherence across long-form generation.
- Regenerative corpora, curated from indigenous wisdom, ecological science, and symbolic cosmologies.
- Novel evaluation metrics, including semantic coherence index (SCI), life-value alignment score (LVAS), and regenerative resonance score (RRS).
We offer practical blueprints for implementation, including fine-tuning open-source LLMs, retrofitting attention mechanisms, and creating a distributed regenerative AI ecosystem.
The paper concludes by reframing the purpose of AI: not to dominate or displace human intelligence, but to apprentice to the symbolic intelligence of life — and help humanity reweave a broken world through language that heals.