How Much Data Did ChatGPT Use to Do Its Training?

ChatGPT is a language model-based chatbot developed by OpenAI. It has advanced capabilities that enable it to refine conversations based on length, format, style, detail, and even language. A significant contributor to ChatGPT's abilities is the vast amount of data it was trained on. This article explores the training data sources and the scale of data collection for ChatGPT.

Training on an Enormous Scale

OpenAI trained ChatGPT on a vast amount of text data. According to the OpenAI Cookbook, this model was trained on over 45 terabytes of text data. This extensive dataset includes a variety of sources such as books, articles, web pages, and other text formats.

The training data combines both structured and unstructured data, allowing the model to learn from diverse text types. Such a wide range of training data is crucial for enabling ChatGPT to generate contextually relevant and coherent responses.

A Glimpse into the Training Process

During training, a subset of data is selected for the language model. For GPT-3, the foundational model of ChatGPT, the training data spanned several years. The data was compressed to 45 terabytes of plain text, which was then filtered down to 570 gigabytes.

The training corpus came from varied content sources, including books, articles, research papers, and web pages. This diversity helps ChatGPT understand different writing styles and genres.

The Role of Stack Overflow Data

A common question is whether ChatGPT was trained on Stack Overflow data. Stack Overflow is a well-known platform for technical Q&A among programmers. However, it appears that Stack Overflow data was not directly used in training ChatGPT.

Discussions on AI Stack Exchange raised this question, but no clear mention of Stack Overflow data as part of the training set has been made. The primary sources for training were the previously mentioned materials, such as books and articles.

The Cost and Time of Training

Training a language model on such a large dataset requires substantial resources. For ChatGPT, the reported training cost was \$43,000, reflecting the significant computational power needed.

Training duration is also considerable, though specific time details for ChatGPT are not provided. It is clear that developing a model of this scale demands both time and computational resources.