What is Chain-of-Thought?

Artificial intelligence (AI) continues to advance by leaps and bounds, and one of the most innovative techniques that is gaining ground is "chain of thought". This technique not only enhances the cognitive capabilities of AI models, but also facilitates the interpretation of their internal workings, representing a major step towards more transparent and reliable models.

In this article, we will explore what "chain-of-thought" is, how it works, and why it is important. Additionally, we will use a clear and detailed example to illustrate its functioning in an easy-to-understand way.

What is "Chain-of-Thought"?

Chain of thought in AI refers to breaking down complex problems into smaller, more manageable stages or steps. This structured approach allows AI models to tackle and solve challenges that were previously too intricate. It is similar to how a human would mentally break down a problem before solving it, step by step.

Similar to the succession of mental connections that form as we progress in our thought process, chain-of-thought can be linear, where thoughts connect one after another, or branched, where thoughts diverge in different directions.

How Does "Chain-of-Thought" Work?

Chain-of-thought starts with an initial thought, which can be a question, a problem, or an idea. From this initial thought, our mind tends to connect it with other related or derived thoughts or ideas. This succession of thoughts or mental connections can occur quickly and automatically, or it may require a deeper process of reflection. As we progress in our thought process, new thoughts connect with previous ones, forming a chain of interconnected ideas.

Practical Example

Let's consider a mathematical problem similar to the one illustrated in the promptingguide.ai guide, simple but requiring several steps of reasoning: determining if the sum of odd numbers in a group results in an even number. Through the chain-of-thought technique, an AI model could approach this problem as follows:

Question: Does the sum of the odd numbers in this group result in an even number? Group of numbers: 15, 32, 5, 13, 82, 7, 1.

Step-by-step reasoning:

1. Identify the odd numbers in the group: 15, 5, 13, 7, 1.

2. Add up these numbers: 15 + 5 + 13 + 7 + 1 = 41.

3. Determine if the result (41) is even or odd.

Result: The sum of the odd numbers is 41, which is an odd number. Therefore, the statement is false.

This example illustrates how chain-of-thought allows AI to break down the problem into understandable steps, facilitating the verification of each stage of the process and the explanation of the final result.

Why "Chain-of-Thought" is Key in the Effective Use of ChatGPT

Chain-of-thought is essential in interacting with ChatGPT because it helps maintain clear and coherent communication. When interacting with ChatGPT, it is important to maintain a logical structure in questions or comments so that the model can understand and respond appropriately. If the chain of thought is broken or becomes confusing, the responses generated by the model may be incoherent or irrelevant.

A clear example of how chain-of-thought is important in the use of ChatGPT is when a series of questions are asked or information is provided in multiple stages.

For example, suppose you are interacting with ChatGPT to get information about a recipe. If you ask an initial question about the ingredients, followed by a question about the preparation steps, and then a question about the cooking time, it is essential to maintain a clear and sequential chain-of-thought so that the model can understand and respond appropriately to each question.

Chain of thought is setting a new standard for AI development, promoting models that are not only powerful but also understandable and reliable. As this technique is perfected and more widely adopted, we are likely to see AI even more integrated into everyday solutions, improving from complex automated systems to intelligent personal assistants.