Understanding the difference between Machine Learning and Artificial Intelligence ~ 30 April 2018

Artificial Intelligence (AI) and Machine Learning (ML) are two very hot buzzwords right now, and often seem to be used interchangeably.

They are not quite the same thing, but the perception that they are can sometimes lead to some confusion. Both terms crop up very frequently when the topic is Big Data, analytics, and the broader waves of technological change which are sweeping through our world.

The best answer is that Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”.  AI can refer to anything from a computer program playing a game of chess, to a voice-recognition system like Amazon’s Alexa interpreting and responding to speech.

Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves. It’s currently the most promising tool in the AI kit for businesses. ML systems can quickly apply knowledge and training from large data sets to excel at facial recognition, speech recognition, object recognition, translation, and many other tasks. Unlike hand-coding a software program with specific instructions to complete a task, ML allows a system to learn to recognize patterns on its own and make predictions.

Of course machine learning is used in many other areas and for more complicated solutions such as fraud prevention, risk analysis, gaining better customer insight and improving medical science among other uses.

As you can see, AI is basically the ‘intelligence’ or the ‘technology’ while machine learning is the implementation of the computational methods that support it. It is inevitable that we will hear about them more and see further innovations and emerging technologies.

~ An opinion expressed by Sacha Carikas