Editing How AI Actually Works (section)

== Why "trained on text" matters ==

Modern AI models like GPT-4, Claude, and Gemini were trained on enormous amounts of text — books, websites, code, conversations, research papers. During training, the model was repeatedly shown text with a word removed and asked to predict what goes there. Billions of times. Across billions of examples.

This is why AI can write in any style, answer questions about almost any topic, and generate code in dozens of languages. It's seen patterns in all of those domains.

But it also means:
* '''AI doesn't "know" facts.''' It learned that certain words tend to follow other words in certain contexts. When it tells you that Paris is the capital of France, it's not retrieving a fact from a database — it's producing the statistically likely continuation of your question. This is also why it can confidently state things that are wrong. (See: [[Why AI Gets Things Wrong|Why AI Gets Things Wrong]])
* '''Training has a cutoff date.''' The model learned from text up to a certain point. It doesn't know what happened after that unless it has access to search tools or uploaded documents.
* '''It reflects the patterns in its training data.''' Including the biases, the common phrasings, and the popular opinions. AI doesn't have its own perspective — it has a statistical average of human text.