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

Why introduce a public cloud?

At the beginning of this chapter, we saw how Microsoft and OpenAI have partnered in recent years and how Microsoft’s cloud, Azure, became the gym for OpenAI model training. However, it also became the cloud infrastructure where OpenAI models can be consumed.

But what is the difference between using models from OpenAI and Azure OpenAI? The difference is the underlying infrastructure: with Azure OpenAI, you are leveraging your own infrastructure while living in your own secured subscription. This brings a series of advantages:

  • Scalability and flexibility: You can benefit from the scalability of Azure and accommodate the elastic usage of AOAI models. From small pilots to enterprise-level production projects, AOAI allows you to leverage the required capacity and scale up or down if necessary.
  • Security and compliance: You can use role-based authentication and private network connectivity to make your deployment more secure and trusted...