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.
See also
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.
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.
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.
Diffusion Model
A type of generative model that learns to create images (or other content) by gradually "cleaning up" random noise until a coherent picture emerges. It underlies most image generators, including Midjourney, Stable Diffusion, and DALL-E.