What is Chain of thought (COT) vs. One Shot

 Chain of thought is a problem-solving technique where a series of intermediate reasoning steps are explicitly stated before arriving at the final answer. This approach has been shown to improve the performance of language models on complex reasoning tasks.

Here's how the chain of thought process works:

1. Problem decomposition: Break down the complex problem into smaller, more manageable sub-problems or steps.

2. Step-by-step reasoning: Solve each sub-problem or step sequentially, clearly stating the thought process and intermediate results.

3. Combining results: Integrate the solutions to the sub-problems to arrive at the final answer.

4. Verification: Review the chain of thought to ensure logical consistency and correctness.

The main advantage of using chain of thought is that it allows the model to demonstrate its reasoning process, making the solution more transparent and interpretable. It also helps the model keep track of its progress and maintain focus on the relevant information needed to solve the problem.

Here's a simple example of chain of thought for a math word problem:

Question: John has 5 apples. He gives 2 apples to Mary. How many apples does John have now?

Chain of thought:

- John initially has 5 apples

- He gives 2 apples to Mary

- So, the number of apples John has now is: 5 - 2 = 3

Therefore, John now has 3 apples.

Chain of thought has been successfully applied to various tasks, such as arithmetic reasoning, commonsense reasoning, and symbolic reasoning. It has the potential to improve the performance of language models on tasks that require multi-step reasoning and logical thinking.​​​​​​​​​​​​​​​​