How GPT-3 Processes Language

Next-word prediction is a major part of GPT-3’s training process, which is influenced by a wide range of online text data. During training, the model’s parameters were adjusted to reduce the gap between the predicted and recorded next words in the training set.

When the model is in the inference phase of text generation, it takes in a prompt or prompt prefix and utilizes its knowledge of the language to make a prediction about the next word in the sequence. Iterations of this procedure are performed until some stopping requirement is met, such as the string reaching its maximum length or a given character, such as a period (“. “), being generated.

With over 175 billion parameters, GPT-3 is able to accurately reflect a wide variety of relationships and patterns found in the linguistic data it was trained on. As a result, the text it produces can often be mistaken for that written by a human.