Embedding
A numeric representation of text, an image, or another object as a vector, where semantic similarity between objects is reflected in the closeness of their vectors. It's used to find similar documents and underlies RAG and vector databases.
See also
Context Window
The maximum amount of text (measured in tokens) a model can "see" at once — including the prompt itself, the conversation history, and any attached files. The larger the window, the longer the documents the model can process in one go.
Token (AI)
The smallest unit of text a language model processes — usually part of a word, a whole word, or a punctuation mark. Usage costs for most AI models are billed by the number of input and output tokens.
Inference
The process of using an already-trained model to generate a response to a new input — as opposed to training, when the model adjusts its parameters. Inference is what happens every time you send a message to a chatbot.
AI Agent
An LLM-based system that can not only answer questions but also independently plan steps, call external tools (search, code, APIs), and carry out multi-step tasks to reach a goal with minimal human involvement.
Multimodal AI
A model that can understand and/or generate multiple types of data at once — text, images, audio, and video — rather than just text. For example, it can analyze a photo and answer a question about it in text.
RLHF (Reinforcement Learning from Human Feedback)
A fine-tuning method where humans rate the quality of a model's responses, and the model is adjusted to more often produce answers that humans rate highly. It's a key step in making an AI model helpful and safe, not just technically functional.