AI glossary · AI basics
AI model
An AI model is the trained program at the heart of an AI tool: it takes an input, such as a question or a photo, and produces an output.
Also called machine learning model, model
In more detail
A model is what you get after a learning algorithm studies training data. The patterns it learned are stored as millions or billions of numbers called parameters.
One model can power many products. For example, a single large language model might sit behind a chatbot, a writing app and a coding tool. Using a trained model to get an answer is called inference.
Example
GPT, Gemini and Claude are families of AI models. ChatGPT is an app that lets you talk to OpenAI’s GPT models.
Related terms
ParametersParameters are the internal numbers an AI model learns during training. A model’s size, such as “70 billion parameters”, counts them.Training dataTraining data is the set of examples, such as text, images or past records, that an AI model learns from. Its quality and range shape what the model can do.InferenceInference is when a trained AI model is used to produce an answer, such as a chatbot writing a reply, as opposed to the training stage when it learns.Large language model (LLM)A large language model (LLM) is an AI model trained on vast amounts of text to understand and generate language. It powers chatbots like ChatGPT.
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