What is Chain of Thoughts (CoT)? Process and Variants

Introduction

What is Chain of Thoughts (CoT)?

Chain of Thoughts (CoT) is a cognitive process where individuals or artificial intelligence (AI) models engage in a series of connected thoughts to arrive at a conclusion or solve a problem. It’s essentially a mental pathway where one idea leads naturally to the next, forming a chain that helps clarify complex concepts or tasks.

Why is Chain of Thoughts (CoT) important?

CoT is important because it allows the AI to evaluate multiple factors and ensure that all angles of a problem are considered. This leads to better decision-making and more accurate outcomes.

How Does Chain of Thought Prompting Work?

Chain of Thought Prompting is a technique that guides an AI model to break down a complex task into smaller, step-by-step actions. Rather than directly providing a solution, CoT prompts the system to reason through the problem step by step.

The Step-by-Step Process

Step1: Initial Prompt

The AI is given an initial prompt, which is typically a question or task that needs to be addressed. This prompt serves as the starting point, guiding the AI to begin its thought process.

Step 2: Breaking Down the Task

Once the prompt is given, the AI breaks the task into smaller, more digestible steps. This step-by-step breakdown allows the AI to focus on individual elements of the problem without feeling overwhelmed.

Step 3: Sequential Thinking

As the AI moves from one step to the next, each thought logically builds on the previous one. This ensures a smooth progression of ideas, allowing the AI to maintain clarity and coherence throughout the process.

Step 4: Final Answer

Once the AI has worked through all the steps, it puts everything together to arrive at a final answer. This outcome is a culmination of the logical sequence it followed, leading to an informed conclusion.

Difference Between Prompt Chaining and Chain of Thoughts (CoT)

Understanding Prompt Chaining

Prompt chaining refers to providing the AI with several prompts, where each one follows from the last answer. This is typically a series of independent actions, rather than a connected chain of thought.

How CoT Differs from Prompt Chaining

CoT differs because it focuses on a continuous, logical flow of ideas, where one thought directly leads to the next. In prompt chaining, the model may jump between different ideas without building a continuous thread of reasoning.

Chain of Thought Prompting Examples

1. Math Word Problem

Prompt: If a pen costs $4 and a pencil costs $5, how much do 3 pens and 3 pencils cost?

Chain of Thought:

First, calculate the cost of 3 pens: 3 × $4 = $12.

Then, calculate the cost of 3 pencils: 3 × $5 = $15.

Now add both totals: $12 + $15 = $27.

Answer: $27

2. Logical Reasoning

Prompt: John is taller than David. David is taller than Sam. Who is the shortest?

Chain of Thought:

John > David > Sam means Sam is shorter than both John and David.

Answer: Sam is the shortest.

3. Factual + Inference

Prompt: Whales are mammals and need air to breathe. If a whale is underwater for too long, what will happen?

Chain of Thought:

Whales breathe air, not water. If they stay underwater too long, they can’t breathe.

So they must surface to get air.

Answer: The whale will run out of air and need to surface to breathe.

4. Date Calculation

Prompt: If today is Monday and you have a meeting in 10 days, what day will it fall on?

Chain of Thought:

10 days from Monday = Monday + 7 (one full week) = Monday, then add 3 more days = Thursday.

Answer: Thursday

5. Common Sense Decision Making

Prompt: You forgot your umbrella and it’s starting to rain. There’s a shop nearby selling umbrellas for $5. What should you do?

Chain of Thought:

If I don’t buy the umbrella, I’ll get wet.

I need to stay dry and $5 is affordable.

Buying the umbrella is the smarter choice.

Answer: Buy the umbrella.

Variants of Chain of Thought

1. Simplified CoT

Simplified CoT is used for basic tasks that don’t require much complex reasoning. It breaks down the problem into a few simple steps, making it easy to follow and solve quickly.

2. Advanced CoT

Advanced CoT is for tackling more difficult problems that need deeper analysis. It involves multiple steps, with each one exploring different aspects of the problem to come to a more detailed and thoughtful solution.

3. Hybrid CoT

Hybrid CoT combines traditional CoT with external information or additional tools. Using extra data sources or other models helps the AI think more deeply and reach more accurate conclusions.

Advantages of Chain of Thought Prompting

Improved Accuracy in Responses

CoT encourages AI models to reason step-by-step. It leads to more accurate and well-structured responses, particularly in tasks requiring logical progression or multi-step solutions.

Facilitating Complex Problem-Solving

By breaking down a complex task into smaller, manageable components, CoT makes it easier to solve problems that would otherwise be difficult to tackle in a single step.

Limitations of Chain of Thought Prompting

Overcomplicating Simple Tasks

For simpler problems, CoT can sometimes overcomplicate the process, leading to unnecessary steps or convoluted thinking when a straightforward solution would suffice.

Dependency on Quality of Input

The quality of the input plays a major role in how well CoT performs. If the initial prompt is unclear or ambiguous, the entire chain of thoughts can become flawed.

Use Cases of CoT Prompting

AI Models for Enhanced Language Understanding

In language models, CoT helps improve understanding by making the system follow a logical sequence of ideas, making responses more natural and contextually appropriate.

Problem-Solving and Decision-Making

In decision-making processes, such as financial analysis or strategy development, CoT helps evaluate various scenarios, ensuring that each factor is carefully considered.

Creative Writing and Content Generation

In writing, CoT helps break down complex ideas into manageable parts, allowing for more structured, creative, and coherent storytelling or content creation.

FAQ

1. What is the chain of thought in NLP?
   Chain of Thought (CoT) is a prompting technique that encourages models to break down problems step-by-step before giving the final answer.
2. Is CoT only useful for math problems or logical reasoning tasks?
   No, while it’s popular for math and logic, CoT also improves performance in tasks like reading comprehension, commonsense reasoning, and more.
3. What’s the difference between standard prompting and CoT prompting?
   Standard prompting asks for a direct answer. CoT prompting helps the model think out loud before giving an answer.
4. Can Chain of Thought be used with all models (e.g., GPT, Claude, Gemini)?
   It works best with large language models trained on reasoning tasks. Most advanced models like GPT-4, Claude, and Gemini support CoT effectively.
5. What’s the difference between few-shot and zero-shot Chain of Thought?
   Zero-shot CoT prompts the model to think through a task without any examples, whereas few-shot CoT gives the model a few examples to illustrate how to reason through problems.