The Magic Behind AI Responses: How Language Models Really Work
When you type a question and hit “go,” you’re triggering something remarkable—years of research, training, and technology come together to generate a response in seconds. Tools like ChatGPT or DeepSeek-R1 don’t “understand” your question like a person would. Instead, they look at your words and predict what should come next, one piece at a time. This ability comes from three key stages: Pretraining, Supervised Fine-Tuning, and sometimes Reinforcement Learning. It starts with your question getting broken down into small parts—called tokens. These could be words or even pieces of words. The model treats this as the beginning of a sentence and starts filling in the rest, one token at a time. The response you see isn’t pulled from a database or a Google search. It’s generated on the fly, based on how the model has been trained to “sound” helpful. ...