Book Image

Modern Generative AI with ChatGPT and OpenAI Models

By : Valentina Alto
4.9 (8)
Book Image

Modern Generative AI with ChatGPT and OpenAI Models

4.9 (8)
By: Valentina Alto

Overview of this book

Generative AI models and AI language models are becoming increasingly popular due to their unparalleled capabilities. This book will provide you with insights into the inner workings of the LLMs and guide you through creating your own language models. You’ll start with an introduction to the field of generative AI, helping you understand how these models are trained to generate new data. Next, you’ll explore use cases where ChatGPT can boost productivity and enhance creativity. You’ll learn how to get the best from your ChatGPT interactions by improving your prompt design and leveraging zero, one, and few-shots learning capabilities. The use cases are divided into clusters of marketers, researchers, and developers, which will help you apply what you learn in this book to your own challenges faster. You’ll also discover enterprise-level scenarios that leverage OpenAI models’ APIs available on Azure infrastructure; both generative models like GPT-3 and embedding models like Ada. For each scenario, you’ll find an end-to-end implementation with Python, using Streamlit as the frontend and the LangChain SDK to facilitate models' integration into your applications. By the end of this book, you’ll be well equipped to use the generative AI field and start using ChatGPT and OpenAI models’ APIs in your own projects.
Table of Contents (17 chapters)
1
Part 1: Fundamentals of Generative AI and GPT Models
4
Part 2: ChatGPT in Action
11
Part 3: OpenAI for Enterprises

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...