Chain of Thought (CoT) reasoning in AI systems is a cognitive-inspired framework that improves the performance of large language models (LLMs) by explicitly guiding the AI through intermediate reasoning steps.
Advantages of Chain of Thought:
- Improved Interpretability: Since the model outputs intermediate steps, it’s easier for humans to understand how the final answer was reached.
- Better Performance on Complex Tasks: CoT allows the model to handle multi-step reasoning more effectively.
- Easier Debugging: If there’s an error in reasoning, it can be spotted at a specific step in the chain, which aids in model fine-tuning and debugging.