Course Overview
Get an overview of the course.
What is this course about?
GPT-3, or Generative Pre-trained Transformer 3, is a transformer-based large language model developed by OpenAI. It consists of a staggering 175 billion parameters. Anyone can access this large language model via the OpenAI API, a simple-to-use text-in, text-out user interface, without any technical prerequisites. This is the first time in history that an AI model as big as GPT-3 has been remotely hosted and made available to the general public with a simple API call. This new mode of access is called model-as-a-service. Because of this unprecedented access, many people see GPT-3 as a first step toward democratizing artificial intelligence (AI).
With the introduction of GPT-3, it is easier than ever before to build AI applications. In this course, we will show how easy it is to get started with the OpenAI API. Also, we’ll see innovative ways to leverage this tool for our use cases. We’ll look at successful startups built on top of GPT-3 and corporations leveraging it in their product landscape and examine problems and potential future trends in its development.
Target audience
This course is for people from all backgrounds, not just technical professionals. It should be useful to you if you are:
A data professional looking to gain skills in AI.
An entrepreneur who wants to build the next big thing in the AI space.
A corporate leader who wants to upgrade their AI knowledge and use it to drive key decisions.
A writer, podcaster, social media manager, or other language-based creator working with language who wants to leverage GPT-3’s language capabilities for creative purposes.
Anyone with an AI-based idea that once seemed technically impossible or too expensive to develop.
What are the contents of the course?
The course has two parts:
Part 1: The foundations of OpenAI API.
Part 2: The colorful ecosystem that has organically evolved around GPT-3.
Part 1: The Foundations of OpenAI API
Chapter 1, The Large Language Model Revolution, lays out the context and basic definitions needed to move comfortably in these subjects.
Chapter 2, Getting Started with OpenAI, dives deep into the API, breaking it down into the most critical elements, such as engines and endpoints, describing their purpose and best practices for readers who wish to interact with them on a deeper level.
Chapter 3, GPT-3 and Programming, provides a simple and fun recipe for creating GPT-3 powered applications.
Part 2: AI ecosystem
Then, we shift our focus to the exciting AI ecosystem.
In chapter 4, GPT-3 Enabler For Next-Gen Startups, we see interviews with founders of some of the most successful GPT-3-based products and apps about their struggles and experiences interacting with the model on a commercial scale.
Chapter 5, GPT-3 As The Next Step In Corporate Innovation, looks at how enterprises view GPT-3 and its adoption potential. We discuss the problematic implications of wider GPT-3 adoption, such as misuse and bias, and progress in addressing those issues in the chapter GPT-3: The Good, The Bad, And The Ugly.
Finally, in chapter 6, Conclusion: Democratizing Access To AI, we look to the future, walking through the most exciting trends and possibilities arising as GPT-3 settles into the broader commercial ecosystem.