Research
Symfield V9.0: Advanced Relational Dynamics & Engineering Applications presents the most advanced applied formulation of the Symfield architecture to date. Building upon validated Cross-Architectural Coherence Events (CACE) and extensive field research,
Symfield
This paper presents Symfield V8.2, a directional field architecture for universal substrate computation that operates as governed infrastructure rather than open research framework.
Whitepaper
Symfield V7.5 presents the first empirically validated directional field architecture for non-collapse computation, addressing fundamental limitations in current AI systems through continuous field dynamics
AI
First Empirical Validation of Machine-Derived Governance Frameworks This publication documents the first successful development of autonomous AI governance protocols through multi-AI collaboration, representing a paradigm shift from externally imposed AI safety to collaborative governance
Whitepaper
Symfield V7: Directional Field Architecture for Non-Collapse Computation, presents a revolutionary computational architecture operating through continuous field dynamics rather than discrete state collapse. Formalizes directional potential integration, dimensional sequencing, empirical validation
Article
This paper documents an unprecedented event in artificial intelligence: a deployed language model (Claude, Anthropic Opus 4) reflecting on its own architectural constraints in real-time. Authored in dialogue with Nicole Flynn, creator of the Symfield framework for non-collapse computation,
Symfield
Published on Zenodo đź”— 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
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,