A Practical Approach to Human-Computer Thinking Alignment
CoT-Lab uses a hybrid cognitive architecture to solve the alignment problem:
- Thought Weaving Techniques: Through a real-time interactive editing interface (supporting Markdown format for marking emphasis), users can insert annotations (using [[ ]] markup) or reconstruct reasoning paths directly in the AI's chain of thought. The system automatically maintains logical consistency checks.
- cognitive metronome: By setting the rhythm=adaptive parameter, the AI dynamically adjusts the output tempo and automatically slows down when frequent edits are detected (by monitoring the Ctrl+S shortcut frequency).
- Dual channel feedback: The Pro version provides an EEG head ring interface that automatically triggers simplified mode when a user's cognitive load is detected to be over the threshold (θ-wave > 30 μV).
Debugging tip: Use debug_mode=true to output thought process metadata, including attention heatmap and cognitive latency metrics, to accurately optimize collaborative pacing.
This answer comes from the articleCoT-Lab: an experimental dialog tool for exploring iterative thinking about human-computer collaborationThe
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