Models
Tree of Thoughts
A prompting framework that has a language model explore several intermediate reasoning steps ("thoughts") as branches of a tree instead of one linear chain.
In depth
A prompting framework that has a language model explore several intermediate reasoning steps ("thoughts") as branches of a tree instead of one linear chain. The model generates candidate thoughts, evaluates them itself, and uses search with lookahead and backtracking to decide which branch to pursue. In the original Princeton and Google DeepMind paper, GPT-4 solved 74% of Game of 24 puzzles with Tree of Thoughts versus 4% with chain-of-thought prompting.
Primary source: arxiv.org
Example
In practice, developers reach for Tree of Thoughts when they need the capability described above as part of an AI feature or workflow.
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FAQ
Common questions
What is Tree of Thoughts?
A prompting framework that has a language model explore several intermediate reasoning steps ("thoughts") as branches of a tree instead of one linear chain.
Why does Tree of Thoughts matter for AI developers?
Tree of Thoughts sits in the Models 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 Tree of Thoughts?
Developers Digest publishes tutorials and videos that cover Models topics including Tree of Thoughts. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Models
Self-Consistency
A decoding strategy that samples several chain-of-thought reasoning paths for the same question and returns the final answer that appears most often.
Models
GSM8K
A dataset of 8,500 grade school math word problems from OpenAI that take several steps of basic arithmetic to solve.
Models
Extended Thinking
A Claude feature that gives the model a dedicated thinking phase before producing its visible response.
Put this concept to work
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