reaperdoesntknow/Symbiotic-8B

SymbioticLM-8B: Hybrid Symbolic–Transformer Model

SymbioticLM-8B, developed by Convergent Intelligence LLC: Research Division, is a unique hybrid model that merges an 8 billion parameter Qwen-based transformer with advanced symbolic cognition capabilities. It features modular symbolic processors and a persistent 2048-vector memory buffer, enabling it to perform complex symbolic reasoning while maintaining high-fidelity language generation.

Key Capabilities

• Hybrid Architecture: Combines a Qwen-8B transformer backbone with specialized symbolic modules like ThoughtDynamicsLNN, CrystallineProcessor, LiquidThoughtProcessor, and HelicalDNAProcessor.
• Persistent Memory: Utilizes a 2048 symbolic vector memory with entropy-aware retrieval for contextual recall and long-term memory retention across interactions.
• Deep Symbolic Reasoning: Designed for tasks such as theorem generation, logical chaining, and structured reasoning, going beyond typical LLM capabilities.
• "Dream Mode": Features an offline self-generation mechanism for symbolic cognition.
• Discrepancy Calculus Foundation: Developed under the DISC framework, which treats training singularities as structural signals for understanding learning geometry.

Good For

• General symbolic reasoning and logical conversation.
• Memory-aware tutoring and research assistant applications.
• Code and mathematical proof modeling.
• Context-persistent dialogue systems requiring retained memory over time.

Limitations

• Not instruction-tuned, which may require prompt engineering for chat-style inputs.
• Larger memory buffer can slightly increase CPU load.
• Symbolic inference is offline-evolved, requiring active memory seeding.