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Plain-English AI glossary

Short definitions to make tool instructions and AI discussions easier to follow.

Generative AI
Models that produce content such as text, images, audio, or code from patterns learned during training.
Large language model (LLM)
A model trained on large amounts of language data to predict and generate sequences of tokens.
Token
A unit a model processes, often a word fragment, character, or punctuation mark.
Context window
The amount of information a model can consider in a single interaction. It is not the same as permanent memory.
Hallucination
An output containing invented or unsupported information, sometimes presented with apparent confidence.
AI agent
A system that uses a model and tools to carry out steps toward a goal, with varying degrees of autonomy.
Retrieval-augmented generation (RAG)
Retrieving relevant source material and supplying it to a model to help inform an answer.
Fine-tuning
Additional training that changes a model’s parameters for a task, style, or domain.
Inference
Running a trained model to produce an output. Distinct from training the model.
AGI
Artificial general intelligence: a term for broadly capable AI, with no single universally accepted threshold.

A few more useful distinctions

Open weights
Model parameters available for download under a license. This does not necessarily include training data or unrestricted commercial rights.
Multimodal
A system that works with more than one kind of input or output, such as text and images.
Embedding
A numerical representation used to compare or retrieve items by patterns of similarity.
Prompt injection
Instructions planted in content an assistant reads, attempting to redirect its behavior beyond the user’s intended task.
Evaluation
A defined process for checking a system against relevant tasks and failure conditions.
Inference cost
The resources spent running a model, distinct from the cost of training it.
Agent permission
The access an assistant has to take actions through connected tools or accounts.