Book Image

AI for Absolute Beginners: A Clear Guide to Tomorrow

By : Oliver Theobald
4 (1)
Book Image

AI for Absolute Beginners: A Clear Guide to Tomorrow

4 (1)
By: Oliver Theobald

Overview of this book

The course begins with an engaging introduction to the world of Artificial Intelligence, making it approachable for absolute beginners. We unravel the mysteries of AI's evolution, from its historical roots to the cutting-edge technologies shaping our future. By explaining complex concepts in simple terms, this course aims to illuminate the path for those curious about how AI impacts our world. The course focuses on the core components of AI, including machine learning, deep learning, and natural language processing, before advancing to more specialized topics like generative AI and computer vision. Each module is designed to build a comprehensive understanding, emphasizing why these technologies are crucial for solving real-world problems and how they're transforming industries. The course wraps up by exploring the ethical considerations and privacy concerns associated with AI, along with a visionary look at the future of work in an AI-driven world. It offers a treasure trove of further resources, ensuring learners have everything they need to continue their exploration of AI.
Table of Contents (13 chapters)
Free Chapter
1
Introduction
2
A Brief History
3
AI Building Blocks
4
The 3 Stages of AI Development
5
Machine Learning
6
Deep Learning
7
Natural Language Processing
8
Generative AI
9
Recommender Systems
10
Computer Vision
11
Privacy & Ethical Considerations
12
The Future of Work
13
Further Resources

Generative AI

 

In the ever-evolving world of AI, a unique variant of machine intelligence is rapidly breaking into software applications and mainstream use. In this chapter, we will explore generative AI, looking at how it differs from its traditional counterpart, and discuss how its rich creativity is changing the landscape of content creation, with a particular focus on generative adversarial networks and the battle for available training data.

First, to understand the strengths of generative AI, it’s important to understand how it differs from traditional AI. The first distinction between generative AI and traditional AI is found in their outputs. Traditional AI, which is sometimes referred to as discriminative AI, is trained to discriminate, classify, or predict based on input data fed into a model. This approach powers a variety of AI applications including recommendation systems and search engines. Generative AI, on the other hand, learns the underlying patterns...