Inference
The process of a trained model predicting on new input — every query you make is inference, which drives API pricing and speed.
AI glossary
What does that AI word actually mean? 16 high-frequency terms, each explained in one direct sentence with the context you'll meet it in.
Embedding
Converting text or images into vectors so semantically similar items land close together in vector space — the foundation of search and RAG.
Vector Database
A database built for storing vectors and fast similarity search, powering retrieval over private knowledge bases.
Temperature
A sampling parameter trading determinism for creativity: low for precise tasks, high for brainstorming.
System Prompt
The upfront instructions that set a model's role, tone and constraints — the real engine behind most wrappers.
Prompt Injection
An attack hiding malicious instructions in text or web content to override a model's original instructions — a security boundary for any app ingesting external content.
Large Language Model
A very large neural network trained on massive text corpora that learns language, knowledge and reasoning by predicting the next token. ChatGPT, Claude and Gemini are all LLMs.
Token
The smallest unit of text a model processes — roughly 0.5–0.75 Chinese characters or 0.75 English words. APIs bill by tokens and context windows are measured in them.
Retrieval-Augmented Generation
Retrieve relevant documents from an external knowledge base before generation. It addresses stale knowledge and hallucination, and is the standard architecture for enterprise Q&A.
AI Agent
An AI system that plans multi-step actions, calls tools and adjusts from feedback. A chat model answers; an agent gets things done — booking trips, fixing code, running analyses.
Fine-tuning
Continuing to train a pretrained model on domain data so its style and capabilities specialize to your task. It changes the model's "instincts" more than RAG does, at higher cost.
Reinforcement Learning from Human Feedback
Humans rank model outputs, those preferences train a reward model, and RL optimizes against it — the key alignment technique that makes LLMs helpful and harmless.
Prompt
The instruction text you give a model. Output quality tracks prompt quality; the four basics are role, context, examples and output format.
Multimodal
A model that understands or generates multiple information types — text, images, audio, video. Photo-based tutoring and voice chat are multimodal abilities.
Hallucination
The model confidently inventing facts, citations or data. No complete cure yet; mitigations include requiring sources, RAG and human review of critical claims.
Context Window
The maximum amount of conversation and documents a model can hold at once, measured in tokens. Bigger windows fit longer docs; mid-window recall remains a common weakness.