BETA RELEASE

Summary

A technical overview of ChatGPT's architecture, explaining GPT's training phases, the Transformer model, response generation via beam search, and the system's advantages and limitations.

Key quotes

GPT (Generative Pre-trained Transformer) technology is a type of machine learning model that is designed to generate natural language text.
The process of training a GPT model involves two stages: Language Modelling... [and] Fine Tuning.
The model uses a technique called beam search to generate multiple possible responses and then scores each response based on its fluency, coherence, and relevance to the input message.

The article provides a high-level technical breakdown of the Generative Pre-trained Transformer (GPT) architecture and the specific training datasets, such as Common Crawl, used by OpenAI. It details the two-phase response generation process consisting of language understanding and response generation.