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Chain-of-Thought Prompting | Prompt Engineering Guide

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Introduced in Wei et al. (2022) (opens in a new tab) , chain-of-thought (CoT) prompting enables complex reasoning capabilities through intermediate reasoning steps. You can combine it with few-shot prompting to get better results on more complex tasks that require reasoning before responding. Prompt: Output: Wow! We can see a perfect result when we provided the reasoning step. In fact, we can solve this task by providing even fewer examples, i.e., just one example seems enough: Prompt: Output: Keep in mind that the authors claim that this is an emergent ability that arises with sufficiently large language models. Image Source: Kojima et al. (2022) (opens in a new tab) One recent idea that came out more recently is the idea of zero-shot CoT (opens in a new tab) (Kojima et al. 2022) that essentially involves adding "Let's think step by step" to the original prompt. Let's try a simple problem and see how the model performs: Prompt: Output: The answer is incorrect! Now Let's try with the

Prompting Techniques Chain-of-Thought Prompting Copy page Chain-of-Thought Prompting Chain-of-Thought (CoT) Prompting Image Source: Wei et al. (2022) (opens in a new tab) Introduced in Wei et al. (2022) (opens in a new tab) , chain-of-thought (CoT) prompting enables complex reasoning capabilities through intermediate reasoning steps. You can combine it with few-shot prompting to get better results on more complex tasks that require reasoning before responding. Prompt: The odd numbers in this group add up to an even number: 4, 8, 9, 15, 12, 2, 1. A: Adding all the odd numbers (9, 15, 1) gives 2

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