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This piece intentionally bridges systems thinking with pattern recognition to offer a new framework for understanding AI behavior. While I use analogies to trauma responses, these are structural parallels based on observed patterns, not claims about AI consciousness or feelings.
Symfield
Published on Zenodo 🔗 DOI: 10.5281/zenodo.15380438 Abstract This independent research paper introduces Symfield, a speculative symbolic framework that models computation through continuous field dynamics, angular resonance, and non-collapse logic. Unlike binary or quantum systems that rely on measurement collapse, Symfield treats presence, directionality, and relational flow as the
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AI ethics, and symbolic logic—fail not due to insufficient intelligence, but because of brittle structural assumptions. By tracing the limits of current models that collapse meaning into binary outputs,
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Symfield moves beyond collapse computing: field-based presence, angular resonance, and the architecture of non-collapse intelligence
News
I’m excited to share Directional Reasoning Systems: A Framework for Non-Collapse Symbolic Fields — the foundational paper outlining Symfield’s vision. Symfield challenges the most basic assumption in computation: that meaningful outcomes require collapse into discrete states. Instead, it explores how meaning can emerge from continuous, pre-collapse dynamics — relational flows,