Prompting
Chain of Thought (CoT)
A prompting technique where the model is asked to show its step-by-step reasoning before arriving at a final answer.
In depth
A prompting technique where the model is asked to show its step-by-step reasoning before arriving at a final answer. CoT improves accuracy on math, logic, and coding tasks by forcing the model to decompose problems rather than jumping to conclusions. Reasoning models like o1 and o3 use chain-of-thought internally as part of their training.
Example
Reasoning models like o1 and o3 use chain-of-thought internally as part of their training.
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Hands-on guides, comparisons, and tutorials that cover Prompting.
FAQ
Common questions
What is Chain of Thought (CoT)?
A prompting technique where the model is asked to show its step-by-step reasoning before arriving at a final answer.
Why does Chain of Thought (CoT) matter for AI developers?
Chain of Thought (CoT) sits in the Prompting part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Where can I learn more about Chain of Thought (CoT)?
Developers Digest publishes tutorials and videos that cover Prompting topics including Chain of Thought (CoT). Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Prompting
Chain-of-Thought Monitoring
Chain-of-thought monitoring uses an automated monitor, often another language model, to read a reasoning model's chain of thought and flag signs that it intends to misbehave, such as reward hacking, sabotage, or deceiving the user.
Prompting
Few-Shot Learning
A prompting technique where you include a small number of input-output examples in the prompt to show the model the pattern you want it to follow.
Prompting
Jailbreak
A jailbreak is a prompt written to get a model to produce output its safety training is meant to refuse.
Put this concept to work
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