What is AI? 4 Key Concepts for Beginners and Mathematicians (Part 1)

Image by Aideal Hwa (@aideal) from Unsplash.com

AI, machine learning, deep learning, neural networks: we see these words everywhere. Yet, differentiating between them is still confusing for many nonspecialists.

In this series of articles, I will attempt to explain each one simply. This would be accessible to non-technically minded readers. I will then provide a mathematical framework for the more technically inclined audience.

The Basics

In simplest terms, we have the following hierarchy:

• AI: simulation of human intelligence by machines and computer systems. The goal of AI is to enable machines to make their own decisions and predictions without needing explicit programming.
• Machine learning: subfield of AI that uses data and algorithms to achieve artificial intelligence in machines.
• Neural networks: sub-field of machine learning, where computer systems are modelled on the human brain and nervous system to aid machine learning algorithms.
• Deep learning: a sub-field of neural networks. To achieve deep learning, multilayered neural networks are used to identify and solve more complex classification problems.

Pictorially, we see the following diagram: