What is chain-of-thought (CoT)?

Chain-of-thought (CoT) is a methodology in the field of large language models (LLM), where the model generates intermediate reasoning or steps to solve a problem before providing the final answer.

The idea is not just to give the answer directly, but to sequentially articulate the logic, which improves the quality and accuracy of the output, especially for complex tasks.

Example:

Instead of answering "42" to the question "What is 6 multiplied by 7?" the model first "thinks":

"6 multiplied by 7 — is 6+6+6+6+6+6+6, that is 7 times 6. 6+6=12, 12+6=18, 18+6=24, 24+6=30, 30+6=36, 36+6=42. Answer: 42."

This approach helps models better handle logical and arithmetic tasks.