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

Understanding Prompt Design

In the previous chapters, we mentioned the term prompt several times while referring to user input in ChatGPT and OpenAI models in general.

This chapter focuses in more depth on the importance of prompt design and engineering as a technique to improve the accuracy of the model. Prompts heavily impact the model’s generated output: a well-designed prompt can help guide the model toward generating relevant and accurate output, while a poorly designed prompt can lead to irrelevant or confusing output. Finally, it is also important to incorporate ethical considerations into the prompt to prevent the model from generating harmful content.

In this chapter, we will discuss the following topics:

  • What is a prompt and why is it important?
  • Zero-, one-, and few-shot learning – typical of transformers models
  • Principles of well-defined prompts to obtain relevant and consistent results
  • Avoiding the risk of hidden bias and taking into...