AWS Certified AI Practitioner (AIF-C01) Study Guide

Chapter 4. Understanding Generative AI

In late 2015, a group of Silicon Valley entrepreneurs—including Elon Musk and Sam Altman—cofounded OpenAI with a mission to ensure that artificial general intelligence (AGI) benefits all of humanity. After initially focusing on reinforcement learning, the company shifted to generative AI, launching the GPT-2 model in 2019. A year later, it released GPT-3, a model with 175 billion parameters trained on 570 GB of text, representing a massive leap from its predecessor.

The turning point came on November 30, 2022, with the launch of ChatGPT. The application’s impact was immediate and transformative, attracting over one million users in its first week and 100 million in two months, making it the fastest-growing software application in history at the time. The success of ChatGPT triggered a surge of investment in generative AI, making the technology a priority for businesses worldwide. This led to the rapid development of new models from competitors, including Google’s Gemini and xAI’s Grok, each pushing the boundaries of the field.

This chapter explores how generative AI works, its core technologies, and its primary use cases.

Neural Networks and Deep Learning

The foundational concepts behind modern generative AI began with early neural networks in the 1950s, which attempted to mirror the human brain. These simple networks had three components:

Input layer

Receives the initial data

Hidden layer

Contains nodes with random weights that process ...