Bicentennial man, Terminator and Ironman. These movies all have one thing in common: Artificial Intelligence. Believe it or not, we are surrounded by this in today’s age and are pretty much dependent on it. And as it grew and developed, terms such as Machine Learning are also brought into the light. More often than not, these two words are used interchangeably and can sometimes lead to confusion. This is why in this article we will discuss the Difference between Artificial Intelligence and Machine Learning.
But first, let us look into how they came to be.
What is Artificial Intelligence?
Artificial Intelligence (AI) has made marvelous breakthroughs since it was first introduced by John McCarthy in 1956. After years of criticisms, disinterest and budget cuts throughout the years, AI emerged to be one of the greatest hallmarks of our technological society.
Artificial Intelligence is the science of making things smart. Simply put, we can see it as human intelligence exhibited by machines; how intelligent machines work and react like humans.
Artificial Intelligence has given birth to different subsets which have now emerged as separate fields all contributing to its breakthroughs. One famous subset of Artificial Intelligence is Robotics. As a major field related to AI, it involves intelligence being programmed into robots in order to handle tasks such as object manipulation and navigation, along with sub-problems of localisation, motion planning and mapping. From healthcare and homecare, to military use and emergency response, we can see how robotics greatly impacts our everyday lives. Robots have worked hand in hand not only for the convenience and comfort of human living but also in increasing their productivity.
Furthermore, Artificial Intelligence can be classified into three categories namely Narrow AI, General AI and Super AI.
Artificial Narrow Intelligence (or Weak AI) is AI that focuses in one area. It aims to equal or exceed human intelligence or efficiency but only in one specific area. Its system is designed to solve specific, well-defined problems. On another note, General Artificial Intelligence refers to a computer that is as smart as a human across the board and that can perform any intellectual task that a human being can. This artificial intelligence’s system is designed to independently learn new tasks and adapt to fast paced environments.
Although we have only reached the Narrow AI, there is no doubt that through continuous and rigorous researches we will make the greatest breakthrough in Artificial Learning.
What is Machine Learning?
Machine Learning, which was introduced a few years after AI, is an approach to achieve artificial intelligence through systems that can learn from experience to find patterns in a set of data, identify similar patterns in future data and make data driven predictions.
For a clearer picture, let’s look at how Machine Learning impacts our ‘Google Experience’.
When you use Google Search, it already anticipates what you might type or search on the internet. It will already give you different suggestions as you start typing your first two words. This depends on your recent searches, what is trending or where you are at the time you are doing your search.
Always had that one word you misspell no matter how hard you try? Well, Google’s use of Machine Learning knows you’re not the only one.
When you accidentally misspell a word while searching in Google, it corrects you by showing the correct spelling of the word with the search results of that word instead of the one you typed.
In this situation we can see how Machine Learning uses the mistakes made by the people, learn from it and try to correct the next person who will commit the same mistake.
Thanks to Machine Learning, Google Mail (Gmail) now gives you a folder of emails which it knows are important to you – Priority Inbox. With Machine Learning, Gmail detects which messages are important to you by looking through which ones you open the most and then separates them from any other messages you receive. As you sift through your inbox, it begins to acquire knowledge on which messages are your priority and those that aren’t.
Pretty handy, don’t you think?
What Is The Difference between Artificial Intelligence and Machine Learning
So how can we really tell AI and ML apart?
Artificial intelligence is a broader concept than machine learning. This involves computers which are programmed to copy or imitate the cognitive function of human brains. On the other hand, Machine Learning is a subset of AI which focuses on how machines are able to use a set of data, learn for themselves and manipulate the algorithms in place as they learn more from the information they are processing. For humans, we learn from experience but in the Machine Learning community they call it ‘data’. And this is the heart of Machine Learning.
Artificial Intelligence can follow instructions like mark an email as spam when it is programmed to, but in Machine Learning like we discussed earlier, it learns which to prioritise based on the preferences of the user.
To further understand the beauty of Artificial Intelligence and Machine Learning. Let’s look at one of the many experiments launched by Google – Quick, Draw.
This game instructs players to draw six different object in a small amount of time while an algorithm in place attempts to guess the object the players are drawing. This 120 second game makes Machine Learning a fun experience for everyone and at the same time widens the knowledge of Google’s Neural Network with these different doodles drawn by netizens around the world. And when it detects something out of the ordinary, it tries to learn and analyse the data it has been given. And give certain corrections based on what it learned from previous players. What are you waiting for? Head on to https://experiments.withgoogle.com/ai and https://teachablemachine.withgoogle.com/ and indulge yourself in a full Artificial Intelligence and Machine Learning experience that will definitely blow your mind.
Things are gonna get even more interesting so check out Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems and bring out the Machine Learning geek in you!