Neural pattern training with SONA (Self-Optimizing Neural Architecture), MoE (Mixture of Experts), and EWC++ for knowledge consolidation. Use when: pattern learning, model optimization, knowledge transfer, adaptive routing. Skip when: simple tasks, no learning required, one-off operations.

Neural Training Skill Purpose Train and optimize neural patterns using SONA, MoE, and EWC++ systems. When to Trigger Training new patterns Optimizing agent routing Knowledge consolidation Pattern recognition tasks Intelligence Pipeline 1. RETRIEVE — Fetch relevant patterns via HNSW (150x 12,500x faster) 2. JUDGE — Evaluate with verdicts (success$failure) 3. DISTILL — Extract key learnings via LoRA 4. CONSOLIDATE — Prevent catastrophic forgetting via EWC++ Components Component Purpose Performance SONA Self optimizing adaptation <0.05ms MoE Expert routing 8 experts HNSW Pattern search 150x 12,500x EWC++ Prevent forgetting Continuous Flash Attention Speed 2.49x 7.47x Commands Train Patterns Check Status View Patterns Predict Optimize Best Practices 1. Use pretrain hook for batch learning 2. Store successful patterns after completion 3. Consolidate regularly to prevent forgetting 4. Route based on task complexity

neural-training