AI Vocabulary · 01 The Model
What is Model?
The trained file of numbers that turns input into output. On its own it can't browse, remember or act.
A model is what training produces: a large file of parameters that turns an input into an output. Give it text, get text back. That is all it does.
Everything else you experience in an AI product, such as searching the web, reading your files, remembering earlier chats or sending emails, is software built around the model. An agent is a model plus that software. A model provider is whoever runs the model for you.
Models come in sizes. Large ones are smarter but slower and more expensive; small ones are faster and cheaper and often good enough for simple jobs.
Why it matters for you
When something goes wrong, the model is not always to blame. The same model behaves very differently depending on what it is given and which tools surround it. Before switching models, check the instructions, the context and the setup.
Own it
Models are replaceable parts. Building your workflows so the model can be swapped, for example a closed model today and an open-weight model tomorrow, keeps you in control.
Where it comes from
The word comes from the Latin modulus, "a small measure". In science, a model has long meant a simplified version of reality. Statistician George Box wrote in 1976 that all models are wrong, a line usually quoted as "all models are wrong, but some are useful", and it is a good motto for AI models too. All models are wrong (Wikipedia)
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