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

Epilogue and Final Thoughts

You’ve made it up to this point – congratulations! I hope you found the book interesting and that it helped you toward your goals.

While writing this book, a number of changes and new developments have occurred that are definitely worth mentioning. We are indeed seeing a development to Moore’s Law in terms of the increasing complexity and accuracy of Generative AI models.

So, in this final chapter, we will briefly recap what we have learned throughout this book, as well as unveiling the most recent developments and what to expect in the near future.

More specifically, we will cover the following topics:

  • Overview of what we have learned so far
  • How LLMs are entering the industries
  • Latest developments in and concerns about the field of Generative AI
  • What to expect in the near future

By the end of this chapter, you will have a broader picture of the state of the art developments within the domain of Generative...