AI, Decoded.
Curiosity welcome.
From prompts to hallucinations, get to know the words behind the technology. Twelve essential AI ideas, explained for curious humans—no computer science degree required.
Artificial intelligence
A broad field concerned with building systems that perform tasks associated with intelligence, such as recognizing patterns, processing language, and making predictions.
Machine learning
An approach to AI in which systems learn patterns from examples rather than relying only on hand-written rules.
Model
A computational system with learned parameters that transforms an input into an output, such as a prediction or generated response.
Training
The process of adjusting a model’s parameters using examples and a learning objective.
Inference
Using a trained model to process a new input and produce an output.
Generative AI
AI that produces content such as text, images, audio, or code based on patterns learned during training.
Large language model
A model trained to process and generate language, typically by learning patterns in sequences of tokens.
Token
A unit a model uses to process information. For text, a token may be a word, part of a word, or punctuation.
Prompt
The instructions, questions, or other input given to a model to guide its response.
Hallucination
An output that sounds plausible but is false, fabricated, or unsupported by the available evidence.
Bias
A systematic tendency in data, model behavior, or decisions that can produce skewed or unfair results.
Human oversight
People reviewing, guiding, and taking responsibility for how AI systems are used and what happens as a result.