What Is The Difference Between AI and Machine Learning?

We at 6S Global use both AI (Artificial Intelligence) and Machine Learning in the services we provide to help your cybersecurity. We thought you might like to know a little more about these processes, so this piece will describe the distinctions between them. 

Actually, ‘difference’ is maybe the wrong word, as Machine Learning is a part of Artificial Intelligence.

Human Intelligence and Learning

Think of the human equivalent of these processes. We might describe human intelligence as a generalised capability to assess and solve problems. This is not specific to any particular kind of problem being presented – rather the ability to  successfully deal with a range of different problems. Human intelligence is based on a creative, open definition of the problem posed, leading to the choice of the most effective tool to solve it. 

Image Artificial Intelligence and Machine Learning Robot

Human learning, on the other hand, is to do with acquiring specific, particular pieces of knowledge or information. For example, learning the order of the alphabet is not in itself a solution, but it becomes an essential technique for sorting and indexing items. We learn items of knowledge to allow ourselves the ability to choose from them to solve problems.

In Computers

In Information Technology, using computers as the engines to enable actions, a similar division exists between Intelligence and Learning – Artificial Intelligence and Machine Learning. 

Artificial Intelligence is the broad range of techniques designed to allow computers to creatively choose the most effective technique for a problem.

Machine Learning is one special technique setting up computers to make their own algorithms for the best processing of data. 


Features of Artificial Intelligence

Features of Machine Learning

Develops understanding of the whole system

Amends processing of specific data

Smart unifying processing

Detailed processing, learning from data

Simulates human intelligence

Processes large amounts of simple data

Makes independent decisions

Improves process to better cope with data

Mimics human thought

Creates self-learning rules

Leads to an overall understanding

Develops the most efficient algorithms

Uses experience to acquire skills to use in  new environments

Uses experience to look for patterns previously learned

Some Experts’ Thoughts

Decades ago, the person who developed some of the fundamental concepts of codable computers, Alan Turing said, “What we want is a machine that learns from experience.”

More recently Andrew Moore, Dean of the School of Computer Science at Carnegie Mellon University, has said, “Artificial intelligence is the science and engineering of making computers behave in ways that, until recently, we thought required human intelligence.”

Also from Carnegie Mellon, Computer Scientist and machine learning pioneer Tom M. Mitchell wrote that “Machine learning is the study of computer algorithms that allow computer programs to automatically improve through experience.”

More Information

We explore both of these concepts in more detail here (for Artificial Intelligence) [Link to piece on AI], and here (for Machine Learning) [Link to piece on Machine Learning].

Get in touch with us and we’ll make sure you’re getting the best from both of these techniques.