LLM
Large Language Model. A neural network trained on massive text data to understand and generate language.
AI Glossary
Quick, practical definitions for common AI terms.
Prompt
The input instruction or context you provide to a model to guide its output.
Token
A chunk of text used by language models for processing and billing. It can be a word, subword, or symbol.
Context Window
The maximum amount of text (in tokens) a model can consider in a single request.
Embedding
A numeric vector representation of text, image, or other data that captures semantic meaning.
RAG
Retrieval-Augmented Generation. A pattern where relevant documents are fetched first and then used in generation.
Fine-Tuning
Further training a base model on a specific dataset so it performs better on targeted tasks.
Inference
The step where a trained model produces predictions or generated outputs for new input.
Hallucination
When a model returns information that sounds plausible but is incorrect or unsupported.
Agent
A system that uses an LLM plus tools, memory, and logic to execute multi-step tasks.
MCP
Model Context Protocol. A standard for connecting AI models to tools, data sources, and external systems.
Latency
The response delay between sending a request and receiving a result.
Alignment
The process of ensuring an AI's goals and behaviors are consistent with human values, ethics, and intended safety protocols.
RLHF
Reinforcement Learning from Human Feedback. A method of training AI where human rankings of model outputs are used to optimize its performance.
Token
The basic unit of text (ranging from a single character to a whole word) that an LLM uses to process and generate language.
Parameters
The internal variables or 'weights' learned by a model during training that determine how it transforms input data into output.
Explainable AI (XAI)
A set of processes and methods that allow human users to comprehend and trust the results and output created by machine learning algorithms.
AGI
Artificial General Intelligence. A theoretical form of AI that possesses the ability to understand, learn, and apply knowledge across any intellectual task a human can do.
Computer Vision
A field of AI that enables computers to derive meaningful information from digital images, videos, and other visual inputs.
Diffusion Model
A type of generative model, often used for image creation, that learns to generate data by reversing a process of adding noise to images.
Multimodal AI
An AI system that can process and relate information from different types of data, such as combining text, images, and audio.
OCR
Optical Character Recognition. The use of AI to convert images of typed, handwritten, or printed text into machine-encoded text.
RAG
Retrieval-Augmented Generation. A technique that enhances LLM responses by retrieving relevant information from an external knowledge base before generating text.
Agent
An AI system designed to use tools, browse the web, or execute code autonomously to achieve a complex goal set by a user.
Vector Database
A specialized database that stores data as numerical vectors, allowing AI models to perform fast similarity searches for relevant context.
Context Window
The maximum amount of information (tokens) an AI model can process or 'remember' at one time during a single conversation.
Fine-Tuning
The process of taking a pre-trained model and further training it on a smaller, specific dataset to adapt it for a particular task or domain.