Foundations

Plain-language explainers of the base vocabulary of AI: what artificial intelligence, machine learning and models are, and how the pieces fit together.

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Foundations

ComparisonTraining vs. InferenceTraining changes an AI model's learned settings so it can perform a task better; inference uses a selected state of that model to produce an output without changing those learned settings. Training creates or adapts the model, while inference puts that model to work.
ConceptWhat Is Artificial Intelligence?Artificial intelligence (AI) is the field of designing computer systems that produce goal-directed outputs—such as predictions, content, recommendations, or decisions—using methods associated with abilities such as learning, reasoning, perception, and language. AI also refers to the systems created by that field.
ConceptWhat Is Generative AI?Generative AI is artificial intelligence that learns patterns in existing data and uses those patterns to produce new content, such as text, images, audio, video, or code. It usually generates that content in response to an instruction or other input.
ConceptWhat Is Machine Learning?Machine learning is a way to build software that learns patterns from examples or feedback and uses those patterns to make useful predictions, decisions, or outputs on cases it has not seen before. It is one approach within artificial intelligence, not a synonym for all AI.