AI Concepts A–Z
This is a plain-English concept index for HowAIModelsWork.com. Use it like a practical glossary: each concept gives you a short explanation and a link to a deeper article or guide.
A
An AI system that may plan steps, use tools and act across a task.
Read more →The attempt to shape AI behavior toward intended human goals and rules.
Read more →A trained system that produces outputs from learned patterns.
Read more →A mechanism that helps a model weigh which parts of the input matter most.
Read more →A structured review of an AI system’s data, measurements and outcomes to find uneven behaviour, weak tests or hidden risks.
Read more →B
Systematic patterns in AI outputs that can come from data, labels, objectives, evaluation choices or the way a system is used.
Read more →A smaller group of training examples processed together during one training step.
Read more →A standard set of tasks or measurements used to compare model performance, with limits on what the score proves.
Read more →C
A prompting style that asks the model to work through steps.
Read more →Splitting documents into pieces so retrieval systems can search them more easily.
Read more →AI systems that process images and visual information.
Read more →The amount of text and information the model can consider at one time.
Read more →A saved version of a model during training that engineers can test, compare or resume from.
Open guide →E
Number-like representations that help AI compare meaning.
Read more →The process of testing a model on chosen tasks, groups and failure cases before or after release.
Open guide →F
A later training step used to adjust a model for a task, behavior or style.
Read more →A way for AI to connect a response to a tool or external action.
Read more →A system-level question about how data, objectives, thresholds and consequences affect different people or groups.
Open guide →G
AI that creates text, images, code, audio or other outputs.
Read more →Connecting an AI answer to source material or external information.
Read more →H
A fluent AI answer that may be wrong, unsupported or invented.
Read more →A visual overlay showing which image regions influenced an AI result, without revealing a human-like thought process.
Read more →L
An internal numerical space where a model represents patterns and relationships between visual or other features.
Read more →A number that measures how far a model’s prediction is from its training target and guides parameter updates.
Read more →M
A model design that activates selected expert parts instead of using everything equally.
Read more →A risk that can appear when models learn too much from AI-generated material.
Read more →P
A feature that can carry information about another characteristic even when that characteristic is not collected directly.
Open guide →R
Retrieval-augmented generation: when AI looks things up before answering.
Read more →A model designed to spend more effort on multi-step problems.
Open guide →Finding source material before generating an answer.
Read more →Reinforcement learning from human feedback, used to shape model behavior.
Read more →S
How a model chooses one possible next token from many possible options.
Read more →Data generated artificially, sometimes by AI systems themselves.
Read more →A faster learned approximation that imitates part of a slower scientific simulation.
Read more →T
A setting that affects how predictable or varied an AI answer may be.
Read more →A small piece of text that an AI model reads or predicts.
Read more →A model architecture behind many modern language models.
Read more →V
A database designed to search by meaning instead of exact keywords.
Read more →AI systems that process or generate spoken language.
Read more →Small numerical image regions or feature groups that let a visual model process a picture in manageable pieces.
Read more →The work of checking whether a promising model result survives independent tests, experiments or real-world use.
Open guide →Want a guided route?
If you prefer a reading order instead of an index, use the AI Learning Paths page.
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