AI basics
Build a clear foundation for everyday AI language.
- Large Language Model
An AI model that understands and generates language.
- Prompt
The question, instruction and context you give an AI.
- Token
A basic chunk of text that a model processes.
- Hallucination
An AI response that sounds plausible but is false or unsupported.
- Transformer
A neural-network architecture that models relationships in sequences and underpins modern LLMs.
- Attention Mechanism
A mechanism that lets a model focus dynamically on the most relevant parts of its input.
- Artificial Intelligence
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Machine Learning
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Deep Learning
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Supervised Learning
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Unsupervised Learning
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Neural Network
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Dataset
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Training Data
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Label
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Model
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Prediction
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Classification
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Computer Vision
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- Natural Language Processing
A core concept for explaining how AI systems learn from data, make predictions or complete tasks.
- BERT
A concept used to represent, process or generate human language with machine-learning models.
- Generative Pre-trained Transformer
A concept used to represent, process or generate human language with machine-learning models.
- Foundation Model
A model architecture or technique that shapes how an AI system represents, generates or retrieves information.
- Data Labeling
A method or artifact used to train a model and adapt its behavior to a task.
- Annotation
A method or artifact used to train a model and adapt its behavior to a task.
- Inference
A setting or system component that affects how a trained model produces and serves outputs.
- Temperature
A setting or system component that affects how a trained model produces and serves outputs.
- Max Tokens
A setting or system component that affects how a trained model produces and serves outputs.
- Latency
A setting or system component that affects how a trained model produces and serves outputs.
- Prompt Engineering
A concept for giving instructions, context, structure or safety boundaries to a generative model.
- System Prompt
A concept for giving instructions, context, structure or safety boundaries to a generative model.
- User Prompt
A concept for giving instructions, context, structure or safety boundaries to a generative model.
- Role Prompting
A concept for giving instructions, context, structure or safety boundaries to a generative model.
- Keyword Search
A component or method used to find, rank and ground information for an AI answer.
- Citation
A component or method used to find, rank and ground information for an AI answer.
- Knowledge Base
A component or method used to find, rank and ground information for an AI answer.
- Tool
A component or pattern for letting an AI system plan, use tools and complete multi-step work.
- Workflow
A component or pattern for letting an AI system plan, use tools and complete multi-step work.
- Prompt Template
A component or pattern for letting an AI system plan, use tools and complete multi-step work.
- Responsible AI
A concept for measuring quality, reliability, risk or responsibility in an AI system.
- Image Generation
A method or capability for working with images, audio, video or multiple data types.
- Text-to-Image
A method or capability for working with images, audio, video or multiple data types.
- Text-to-Video
A method or capability for working with images, audio, video or multiple data types.
- Text-to-Speech
A method or capability for working with images, audio, video or multiple data types.
- Speech-to-Text
A method or capability for working with images, audio, video or multiple data types.
- Optical Character Recognition
A method or capability for working with images, audio, video or multiple data types.
- Stable Diffusion
A method or capability for working with images, audio, video or multiple data types.
- Inpainting
A method or capability for working with images, audio, video or multiple data types.
- Outpainting
A method or capability for working with images, audio, video or multiple data types.
- Video Generation
A method or capability for working with images, audio, video or multiple data types.
- Graphics Processing Unit
An engineering practice or platform component for building, deploying and operating AI systems.
- Vibe Coding
An engineering practice or platform component for building, deploying and operating AI systems.