🚀 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.