These two terms often confuse most of the people. They seem to be quite similar when in fact they are not. If you’re someone who’s looking for the difference between the two, let us explain it for you. Artificial intelligence is the broader concept. Whereas machine learning is a subset of artificial intelligence. To understand the distinction among these terms let us discuss them separately
The easiest way to think of artificial intelligence is in the context of a human. After all, humans are the most intelligent creatures that we know of. AI is a broad branch of computer science. The goal of AI is to create systems that can function intelligently and independently.
AI enables the machines to make decisions on their own and to have human-like behaviour. A self-driving car is an example of AI. Siri and Google assistance that we use is an example of artificial intelligence.
Artificial intelligence is an area that covers anything related to making machines smarter. Whether it’s a smartphone app or a car if you’re making them intelligent, then it’s AI.
Machine learning is a subset of AI. Machine learning provides us with statistical tools to explore the data. Humans learn from their experiences and past mistakes. Whereas machines do what we train them to do. Through machine learning, we want to make the machines think and make a decision on their own using the data that is provided to them.
This idea was first shared back in the 1950’s when Arthur Samuel (the pioneer of computer gaming and artificial intelligence) suggested that what if computers could think on their own. This idea gained more importance recently with the emergence of the internet, and huge amounts of data. Instead of teaching machines to do everything. Machine learning focuses on making machines learn for themselves and think like humans.
Here’s a simple example of how machine learning works. For a health care system if you feed the machine with a large data set of x-ray images along with their descriptions. The machine learning model will look at each image, analyze for similar patterns and classify them. When you’ll feed the program with new images it will compare them with the information it gathered before and look for similarities.
Machine learning came in when it was realized that simple hardcoded algorithms weren’t enough for things like image recognition, etc. The answer to this problem was not just to copy what humans did but copy how humans learned and made decisions. For example, when we’re little we are not born with the ability to read and write. We read books to learn about alphabets and spelling. Then shift to complex ones with time. Same is the case with machines. We feed the machine with a lot of data for it to figure it out and learn.
Machine learning is a branch of AI, that helps in making Artificial Intelligence better. However, AI does not really have to use ML although, it makes it more convenient and easy.
