Summary

In this chapter, we went through the history of OpenAI, its research fields, and the latest developments, up to ChatGPT. We went deeper into the OpenAI Playground for the test environment and how to embed the Models API into your code. Then, we dwelled on the mathematics behind the GPT model family, in order to have better clarity about the functioning of GPT-3, the model behind ChatGPT.

With a deeper understanding of the math behind GPT models, we can have a better perception of how powerful those models are and the multiple ways they can impact both individuals and organizations. With this first glance at the OpenAI Playground and Models API, we saw how easy it is to test or embed pre-trained models into your applications: the game-changer element here is that you don’t need powerful hardware and hours of time to train your models, since they are already available to you and can also be customized if needed, with a few examples.

In the next chapter, we also begin...