Mastering ChatGPT: From Zero to Hero (2/3)

Vikas K Solegaonkar
8 min readMay 30, 2023

As machines push their way into the domain of creative work, it is obvious that the days of the human workforce are numbered. This prediction has led to fear and panic in most of the industry. This series of blogs will help you build your skills — not just to retain your job — but to help you rule the new era of Generative LLMs.

Topics covered

This blog starts with a detailed theoretical introduction, then jumps into practical implementation and code examples. We will cover the following topics in the blog series.

  1. Introduction to ChatGPT, LLM, and Prompt Engineering
  2. Using Open AI API in your apps. Host your own Chatbot on AWS
  3. Host your own LLM on AWS, Amazon Bedrock

I am sure you are excited to continue the journey to the next step.

Practical application

The first blog in the series talks a lot about the glorious possibilities of the wonderland. Now is time to do something and see how it works. We have spent enough time playing with the ChatGPT website. It is time now to peep underneath — to remove the coverings and have more fun with what is inside.

This blog focuses on practical implementation details. So switch the gears and get ready to do it. We will work on a mobile application that uses Generative AI to build a friendly flirty bot. Let us first start with OpenAI.

Using OpenAI

Heard that name? Let us ask ChatGPT for details. Here is the answer I got:

OpenAI is an artificial intelligence research lab made up of both for-profit OpenAI LP and its parent company, the non-profit OpenAI Inc. It was established in December 2015 by Elon Musk, Sam Altman, and a number of other high-profile technology entrepreneurs and researchers. OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity.

AGI refers to highly autonomous systems that outperform humans at most economically valuable work. OpenAI aims to directly build