Most of the AI headlines today are about LLMs, short for Large Language Models.
When we say “tokens” in this context, think of them as little pieces of text — often whole words, sometimes parts of words or punctuation.
An AI language model is a token predictor. It looks at huge amounts of text and learns which pieces of text usually follow others. That’s it. There’s no built-in check for truth. It doesn’t know fact from fiction—it just knows what’s statistically common.
Some people assume you can “train AI for truth.” But there’s no truth label on all the text of the Internet. Even fine-tuning with curated correct examples only adjusts probabilities—it doesn’t change the fact that the model is a probability machine at its core.