🚀 Introducing Symfield: A Framework for Non-Collapse Symbolic Fields, Whitepaper
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, angular resonance, and directional tension across symbolic fields.
✨ Key ideas:
- Meaning through directional + geometric relationships, not fixed tokens
- Sustained potential without collapse, using analog AdEx neurons
- A new approach to ambiguity, transformation invariance, and symbolic persistence
⚙️ Core equation:
𝓡 = ∫_Λ Φ(θ) dθ
where resonant meaning 𝓡 arises from integrated directional potential across the field.
This isn’t a finished product or software—it’s a speculative research framework designed to open conversation across symbolic AI, computational neuroscience, and geometric reasoning.
🛠️ Next steps:
- Collaborate on formal mathematical modeling
- Prototype glyph systems that survive transformation
- Explore field-based experimental setups
If you’re working at the edges of AI, symbolic systems, or continuous computation — let’s connect.