Neural Training Skill
Purpose
Train and optimize neural patterns using SONA, MoE, and EWC++ systems.
When to Trigger
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Training new patterns
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Optimizing agent routing
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Knowledge consolidation
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Pattern recognition tasks
Intelligence Pipeline
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RETRIEVE — Fetch relevant patterns via HNSW (150x-12,500x faster)
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JUDGE — Evaluate with verdicts (success$failure)
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DISTILL — Extract key learnings via LoRA
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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
npx claude-flow neural train --model-type moe --epochs 10
Check Status
npx claude-flow neural status
View Patterns
npx claude-flow neural patterns --type all
Predict
npx claude-flow neural predict --input "task description"
Optimize
npx claude-flow neural optimize --target latency
Best Practices
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Use pretrain hook for batch learning
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Store successful patterns after completion
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Consolidate regularly to prevent forgetting
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Route based on task complexity