AI Basics: History, Concepts and Glossary
Start here if you are new to the subject. How the field got from hand-written rules to models that generate, and the vocabulary — each term defined against the others.
3 articles · start with the first and read in order, or jump to what you need
- 1 · BeginnerA Short History of AI: Rules to Generative ModelsSeventy years in four eras — symbolic AI, statistical machine learning, deep learning and generative AI — and the ideas that waited decades for the hardware.10 min read
- 2 · BeginnerAI vs Machine Learning vs Generative AIAI, machine learning, deep learning and generative AI nest inside each other — and knowing which one you are buying changes what you should expect.6 min read
- 3 · BeginnerAI Terms, DefinedThe vocabulary you need to read a vendor deck without being misled, grouped by what each term is actually about. Definitions only — no hype.8 min read
Common questions: AI Basics
What is the difference between AI, machine learning and deep learning?
They nest. Artificial intelligence is the broad field, including rule-based systems that never learn. Machine learning is the part that learns patterns from data. Deep learning is machine learning using many-layered neural networks, and today’s generative AI is built on deep learning.
When was the term artificial intelligence coined?
In a 1955 proposal by John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shannon for a summer research project at Dartmouth College, which took place in 1956.
Is all AI generative AI?
No. Most AI running in production is not generative — it classifies, scores, forecasts and recommends. Generative AI is the part that produces new content such as text, images and code.