OpenAI. That's the word. There is no stopping to the buzz that OpenAI’s latest GPT-3 model is creating. It draws the attention of everyone since it is designed to be able to understand and generate natural-sounding text in a variety of styles and formats. ChatGPT can be used to generate text responses to user input in real-time, allowing it to participate in conversation, respond to a wide range of topics, and integrate it into a variety of applications, such as chatbots and content generation.

In OpenAI, you can fine-tune GPT-3 in order to create your own custom version of the model tailored to your specific data and applications. Fine-tuning is a mechanism used to adjust models for specific tasks and it is based on the concept of Transfer Learning: A pre-trained model is adapted to a new (specialized) domain, significantly improving model performance and reducing training cost.

In this session I'll demonstrate how to fine-tune GPT-3 so it can answer questions from your own data.