Chain of Thought
Chain of Thought is a technique that lets AI models show their step-by-step reasoning before giving a final answer, much like how humans list their thinking steps when solving a problem.
How it works
It works by guiding large language models (such as ChatGPT) to break complex problems down into a series of intermediate reasoning steps, which significantly improves their accuracy and reliability on math, logic, and common-sense reasoning tasks. At its core, the method mimics the way humans think step by step, helping the model avoid leaps of logic and making its decision-making process more transparent and explainable.
Examples
- 1.When asked a math word problem, an AI no longer jumps straight to the answer; instead, it first lists the known conditions, sets up variables, writes out the equations, and only then calculates the result.
- 2.When analyzing a text for logical fallacies, the AI first explains the meaning of each sentence, then points out any contradictions or inconsistencies it finds.
- 3.When answering questions that require multi-step common-sense reasoning (such as "If it rains tomorrow, what should I bring?"), the AI first reasons about how the weather will affect the trip, then recommends packing rain gear.