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 â 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
âď¸ Core equation:
đĄ = âŤ_Î ÎŚ(θ) dθ
where resonant meaning đĄ arises from integrated directional potential across the field.
This isnât a finished product or softwareâitâs a speculative research framework designed to open conversation across symbolic AI, computational neuroscience, and geometric reasoning.