AI Vocabulary · 01 The Model
What is AI?
A moving label for whatever computers can newly do. Today it mostly means large language models.
"Artificial intelligence" doesn't name one fixed technology. Over the decades it has meant rule-based expert systems, chess computers, spam filters and image recognition. Each time a technique becomes ordinary, people stop calling it AI and the label moves on to the next impressive thing.
Today, when people say AI, they almost always mean large language models and the products built on them: chat assistants, writing tools, coding tools and agents.
Why it matters for you
"AI" in a pitch deck, a vendor offer or a board discussion is too vague to decide anything. The useful question is always: which specific system, doing which specific task, with which data, checked by whom? Asking that turns hype into something you can evaluate.
Own it
Owning your AI starts with naming things precisely. If you can tell a model from an app, and an app from an agent, nobody can sell you "AI" as magic. That precision is the core of AI literacy.
Where it comes from
The phrase "artificial intelligence" was coined by John McCarthy in a 1955 proposal, written with Marvin Minsky, Nathaniel Rochester and Claude Shannon, for a summer research project at Dartmouth College. The workshop took place in 1956 and is often called the founding moment of the field. The proposal hoped for a significant advance within a single summer; the field has kept surprising its founders ever since. Dartmouth workshop (Wikipedia)
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