Foundations
Core concepts that underpin every modern AI system.
AI Agent
An AI agent is a language-model-powered system that plans and executes multi-step tasks by choosing which tools or APIs to call in order to reach a user-defined goal.
AI Tokens
A token is the unit of text an LLM processes — typically 3-4 characters or roughly three-quarters of an English word. Prompts, replies and pricing are all measured in tokens.
API
An API (Application Programming Interface) is a defined set of endpoints and rules that lets one program request functionality or data from another.
Context Window
The context window is the token budget an LLM can read and write within a single request, covering the prompt, retrieved data, previous turns and the response itself.
Embeddings
An embedding is a dense vector produced by a model that maps content into a space where distance corresponds to semantic similarity.
Foundation Model
A foundation model is a large-scale, general-purpose model pretrained on broad data and designed to be adapted to many downstream tasks via prompting, fine-tuning or tool use.
LLM
An LLM is a neural network trained on very large text datasets to predict the next token in a sequence, which enables general-purpose language understanding and generation.
Machine Learning
Machine learning is a discipline within AI in which algorithms learn patterns from data so they can make predictions or decisions without being explicitly programmed for each case.
Multimodal AI
A multimodal model is an AI system that natively understands and/or generates multiple modalities such as text, image, audio and video.
Prompt Engineering
Prompt engineering is the discipline of designing inputs to a language model so its outputs are accurate, useful and repeatable.
Reinforcement Learning
Reinforcement learning is a machine learning paradigm in which an agent learns to make decisions by receiving reward signals for its actions in an environment.
Transformer Model
A transformer is a neural network architecture built around self-attention, which enables efficient modelling of long-range dependencies in sequences.