Would you like to understand the magic behind ChatGPT, a variant of the GPT (Generative Pre-training Transformer) model that can generate human-like text in response to a given prompt?

In this presentation, we will reveal the secrets of ChatGPT, a type of transformer-based neural network architecture that is trained on a large dataset of text and fine-tuned on conversational data. We will explain how ChatGPT works, from the input to the output, and how it uses the transformer to process the prompts.

We then delve into the specifics of the model’s vocabulary, including its size and the corpus from which it is derived. The process of tokenization, a critical step in preparing the input for the model, is also examined in detail.

The core of the presentation focuses on the encoder-decoder structure of ChatGPT, explaining how it leverages the power of transformer models to generate responses. We also discuss the backpropagation algorithm, a key component in training the model.

Finally, we explore the feedback and conversation loops in ChatGPT, which enable the model to maintain a dialogue with users. We also touch upon the use of the Retrieval-Augmented Generation (RAG) model in the context of ChatGPT.

By the end of this presentation, attendees will have gained a comprehensive understanding of the inner workings of ChatGPT, providing valuable insights for those interested in natural language processing and AI development.