Modern AI chat assistants can feel almost magical, producing detailed, coherent answers within seconds. Underneath, the process is a combination of a large language model, a system for turning text into numbers, and careful design choices about how the model responds.
Turning Words Into Numbers
When you type a message, it is first broken into small chunks called tokens, which might be whole words or parts of words. Each token is converted into a list of numbers, called an embedding, that captures something about its meaning and how it relates to other words the model has seen during training.
Predicting One Token at a Time
The model then generates its reply one token at a time, each time calculating a probability for every possible next token based on the conversation so far, and selecting one of the most likely options. This process repeats, token by token, building a full response that reads as a coherent sentence even though it was produced through thousands of individual next-word predictions happening in fractions of a second.
Why Answers Sound Natural but Aren't Always Correct
Because the model is fundamentally predicting plausible text based on patterns learned during training, it can produce answers that sound confident and fluent even when they are factually wrong, a phenomenon often called hallucination. This is why it is important to treat AI chat responses as a helpful starting point rather than an infallible source, especially for specialised or high-stakes topics.