Seeking collaborators to develop a Symbolic Reasoning Language (SRL) — a minimal, token-efficient reasoning framework that could dramatically improve LLM reasoning efficiency. What it is: SRL uses 15 Unicode symbols to represent complete cognitive subroutines (proportionality, cascades, irreversibility, adversarial dynamics, etc.). Each symbol encodes an entire reasoning operation with inputs, logic, and outputs. Current Status: We have a working specification (15 primitives, grammar, composition rules, domain binding) and have tested it across multiple domains. Now we need collaborators to make this a formidable achievement. Why this matters: · 5-15x compression - Could make small models (7B-13B) competitive with frontier models on complex reasoning · Cross-model compatibility - Works because it repurposes existing Unicode characters and programming syntax · Real applications - Already tested for robotics navigation, financial decisions, emergency response · Structured reasoning - Forces quantifiable, testable outputs instead of “feels like” or “optimized” Example transformation: Natural language: “Given our cash runway and the acquisition offer’s terms, we need to consider opportunity costs, downstream effects, and whether we’re solving the right problem…” (52 tokens) SRL: ◊:offer ⧉:runway ⟲:framing ⟁:downstream → ⟠=0.68 (8 tokens) submitted by /u/lil-Zavy
Originally posted by u/lil-Zavy on r/ArtificialInteligence