How chat gpt works

ChatGPT is a conversational language model developed by OpenAI. It is based on transformer architecture and has been trained on a massive amount of text data to generate human-like responses/answers.

Here's how chat gpt works at a high level:

User Input/Question/Query: The model takes user input (user question) in a prompt, which is a string of text that provides context for the response it is going to generate.

Pre-processing: The input prompt is first processed to convert it into a numerical representation that can be fed into the model. This is typically done by tokenizing the input text into words and converting each word into a unique integer (also known as an "index") that corresponds to its representation in a fixed-size vocabulary.

Encoding: The numerical representation of the input prompt is then passed through an encoding layer, which converts it into a fixed-length vector that summarizes the input text.

Attention: The fixed-length vector is then used as the input to the attention mechanism, which allows the model to selectively focus on different parts of the input text while generating its response.

Decoding: Finally, the attention mechanism is used to generate a response one word at a time. At each step, the model generates a probability distribution over the vocabulary for the next word, and the word with the highest probability is selected as the next word in the response. This process continues until a specified stopping condition is reached, such as generating a specific number of words or generating a special end-of-sentence token.

The model has been trained on a huge amount of text data, that allows it to generate response text that is highly coherent and reasonably human-like. However, it is important to note that the model is not capable of truly understanding the meaning of the text/response/answer it generates, and there is a possibility that it may sometimes produce nonsensical or inappropriate responses.