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Reasoning model

As explained in Introduction to Generative AI, Second Edition

A reasoning model is a language model that generates intermediate reasoning steps before producing a final answer, especially for difficult problems.

A reasoning model is a language model that works through intermediate steps before giving its final answer. Rather than responding immediately, it analyzes the question, tries partial solutions, and critiques its own attempts. section 2.7

Reinforcement learning trains models such as o1 to produce long chains of thought (CoT) during inference. The precise training details remain undisclosed. section 2.7

Constraining a poem

Given a request for a four-line poem whose lines begin with the seasons and rhyme, a chat model answers directly. A reasoning model first plans the structure, tests possible rhymes, revises weak choices, and then responds. section 2.7

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Explains the observable reasoning sequence but stops short of disclosing training specifics.
Examples
Illustrates rhyme construction through planning, brainstorming, self-correction, and final poem generation.
What you can do after
Evaluate how intermediate reasoning differs from direct answer generation.
How it connects
Connects language models with reinforcement learning, inference, and chains of thought.

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This explainer was generated by Manning's knowledge graph from the text of Introduction to Generative AI, Second Edition. The section links point to the parts of the book it draws on.