Reasoning
An AI model's ability to think logically, make inferences, draw conclusions, and solve problems that require multi-step thought. Reasoning goes beyond pattern matching to genuine logical analysis.
Why It Matters
Reasoning capability is what distinguishes AI that can handle complex, novel problems from AI that can only regurgitate training data patterns.
Example
A model solving: 'If all roses are flowers, and some flowers fade quickly, can we conclude all roses fade quickly?' correctly answering No (logical fallacy).
Think of it like...
Like a detective solving a case — they do not just match fingerprints (pattern matching) but connect clues, form hypotheses, and draw logical conclusions.
Related Terms
Chain-of-Thought
A prompting technique where the model is encouraged to show its step-by-step reasoning process before arriving at a final answer. This improves accuracy on complex reasoning tasks.
Planning
An AI agent's ability to break down complex goals into a sequence of steps and determine the best order of actions to accomplish a task. Planning involves reasoning about dependencies, priorities, and contingencies.
AI Agent
An AI system that can autonomously plan, reason, and take actions to accomplish goals. Unlike simple chatbots, agents can use tools, make decisions, execute multi-step workflows, and adapt their approach based on results.
Inference
The process of using a trained model to make predictions on new, previously unseen data. Inference is what happens when an AI model is deployed and actively serving results to users.