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. This architecture allows it to perform both general conversation and complex symbolic tasks, maintaining persistent memory across interactions.

Key Capabilities & Architecture

• Hybrid Design: Combines a Qwen-8B rotary transformer backbone with specialized symbolic modules like ThoughtDynamicsLNN, CrystallineProcessor (DNAConv GNN), LiquidThoughtProcessor, and HelicalDNAProcessor.
• Persistent Memory: Features a 2048 symbolic vector memory buffer with entropy-aware retrieval and contextual recall, enabling long-term memory for reasoning tasks.
• Symbolic Reasoning: Designed for deep symbolic tasks including theorem generation, logical chaining, and structured reasoning.
• "Dream Mode": Includes a unique feature for self-generating symbolic cognition offline.
• Foundation: Developed under the Discrepancy Calculus (DISC) framework, which treats training singularities as structural signals for understanding learning geometry.

Intended Use Cases

• General symbolic reasoning and logical conversation.
• Memory-aware tutoring and research assistant applications.
• Modeling for code and mathematical proofs.
• Context-persistent dialogue systems requiring long-term memory.

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 seeding of memory.