AI Reference 030 Classical AI & Machine Learning Wikipedia guided Primary sources linked

Artificial Intelligence vs Machine Learning

Definition

Artificial intelligence is the broader field concerned with systems performing tasks associated with intelligent behavior; machine learning is a major subfield in which systems learn patterns from data.

What is artificial intelligence?

Artificial intelligence is the broad field concerned with building systems that perform tasks associated with intelligence: reasoning, planning, perception, language, learning, decision-making and action.

What is machine learning?

Machine learning is a subfield of AI in which systems improve performance by learning statistical patterns from data. Supervised learning, unsupervised learning and reinforcement learning are major machine-learning settings.

The hierarchy of terms

AI is broader than machine learning. Symbolic logic, search and planning can be AI without being learned from data. Deep learning is a subfield of machine learning based on multi-layer neural networks. Large language models are one modern application of deep learning, not a synonym for AI as a whole.

Related terms, defined

Classical AI & Machine Learning Symbolic AI Symbolic AI represents knowledge with explicit symbols, rules and structures, then manipulates those representations with logic, search or planning procedures. Classical AI & Machine Learning Search Algorithms in Artificial Intelligence AI search algorithms explore possible states or actions in order to find paths, plans or solutions. Classical examples include breadth-first search, depth-first search and A*. Classical AI & Machine Learning Heuristics and Problem Solving A heuristic is an estimate or rule used to guide search toward promising states without exhaustively checking every alternative. Classical AI & Machine Learning Knowledge Representation Knowledge representation studies how facts, relations, rules and concepts can be encoded so a computer system can reason over them. Classical AI & Machine Learning Expert Systems Expert systems are narrow rule-based programs that separate a knowledge base from an inference mechanism to reproduce parts of specialist decision-making.

Reference guide and primary sources

Wikipedia is used here as a terminology and history reference guide. Current model versions, institutional statistics and product-specific claims are also linked to first-party or institutional sources because those details can change faster than encyclopedia articles.

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