3 min read

Chain of Thought

Chain of Thought

🧠 Chain of Thought: A Problem-Solving Approach 🧠

What is the Chain of Thought Principle?

  • It's a systematic approach to problem-solving where a complex problem is broken down into smaller, more manageable problems.
  • Each smaller problem is solved sequentially, and the solutions are combined to address the main problem.

How to Apply the Chain of Thought Principle:

  1. Introduce the Problem: Start by understanding the main problem without immediately jumping to a solution.
  2. Break Down the Problem: List down the smaller problems or steps that need to be addressed to solve the main problem.
  3. Solve Each Smaller Problem: Tackle each smaller problem one by one. If uncertain about an answer, make an educated guess.
  4. Compile the Information: Once all smaller problems are solved, gather all the information.
  5. Provide the Final Solution: Combine the solutions of the smaller problems to solve the main problem.

Pasteable Replication for Chat/Project/Task:

1. **Main Problem**: [Describe the main problem here]
2. **Breakdown**:
   - Problem 1: [Describe the first smaller problem]
   - Problem 2: [Describe the second smaller problem]
   ... [Continue listing down the smaller problems]
3. **Solutions**:
   - Solution to Problem 1: [Provide the solution]
   - Solution to Problem 2: [Provide the solution]
   ... [Continue listing down the solutions]
4. **Final Solution**: [Combine the solutions to provide the final answer to the main problem]

Example:

1. **Main Problem**: Determine the country of origin of an object that a cartoon character frequently held in his hands.
2. **Breakdown**:
   - Problem 1: Identify the cartoon character.
   - Problem 2: Identify the object the cartoon character holds.
3. **Solutions**:
   - Solution to Problem 1: Leonardo from Teenage Mutant Ninja Turtles.
   - Solution to Problem 2: Katana.
4. **Final Solution**: The country of origin of the katana is Japan.

Conclusion: The Chain of Thought principle is a powerful tool for tackling complex problems. By breaking problems down and addressing them step-by-step, we can arrive at effective solutions.


ENHANCED VERSION:

1. Introduce the Problem Without Solving It Immediately

 Prompt: "Without solving the problem just yet, think through this carefully and list systematically and in detail all the problems in that riddle that need to be solved before we can arrive at the correct answer."

Problem/riddle: The problem revolves around Michael, who is reminded of a cartoon character from his childhood while looking at a painting in a museum. The challenge is to determine the country of origin of an object that the cartoon character frequently held in his hands.

 Instead of attempting to solve the problem directly, break it down into a series of smaller problems.

2. Break Down the Problem into Smaller Problems

   For given problem about Michael and a cartoon character, smaller problems are:

     1. Identify Michael's location.

     2. Identify the most famous painting.

     3. Identify the artist of the painting.

     4. Determine Michael's favorite cartoon character.

     5. Identify the object the cartoon character holds.

 

3. Solve Each Smaller Problem Sequentially

   For each smaller problem, use a prompt like:

    "With the highest probability you can give, solve [specific problem]."

    - Example: "With the highest probability you can give, identify Michael's location."

 

Sequential thought process:
Michael is likely at the Louvre Museum in France.
The most famous painting is the Mona Lisa by Leonardo da Vinci.
The artist is Leonardo da Vinci.
The cartoon character is likely Leonardo from the Teenage Mutant Ninja Turtles, named after the Renaissance artist.
Leonardo from TMNT holds a katana
 

4. Make Educated Guesses When Necessary

   If the AI isn't certain about an answer, prompt it to make an educated guess.

     - Example: "Provide the cartoon character with the highest probability."

5. Compile the Information

   Once all smaller problems are solved, prompt the AI to compile the information.

     - Example: "Do you have all the info you need now to solve the problem?" 

6. Provide the Final Solution

   Prompt: "List the problems and the final solution."