Machine Learning and Artificial Intelligence: Back to Fundamentals

Both Machine learning and artificial intelligence are frequent phrases used in the discipline of computer science. Nevertheless, there are some variations between the two. In this article, we are going to talk in regards to the differences that set the 2 fields apart. The variations will provide help to get a better understanding of the two fields. Read on to find out more.

Overview

Because the name suggests, the term Artificial Intelligence is a combo of two words: Intelligence and Artificial. We know that the word artificial points to a thing that we make with our hands or it refers to something that is not natural. Intelligence refers back to the ability of people to think or understand.

To start with, it’s important to keep in mind that AI isn’t a system. Instead, in refers to something that you implement in a system. Although there are a lot of definitions of AI, one among them may be very important. AI is the research that helps train computer systems with a view to make them do things that only humans can do. So, we kind of enable a machine to perform a task like a human.

Machine learning is the type of learning that enables a machine to learn on its own and no programming is involved. In different words, the system learns and improves automatically with time.

So, you’ll be able to make a program that learns from its experience with the passage of time. Let’s now take a look at a few of the main variations between the 2 terms.

Artificial Intelligence

AI refers to Artificial Intelligence. In this case, intelligence is the acquisition of knowledge. In other words, the machine has the ability to get and apply knowledge.

The first goal of an AI based system is to increase the likelihood of success, not accuracy. So, it doesn’t revolve round growing the accuracy.

It includes a computer application that does work in a smart way like humans. The goal is to boost the natural intelligence with a view to clear up loads of complex problems.

It is about resolution making, which leads to the development of a system that mimics people to react in certain circumstances. Actually, it looks for the optimum resolution to the given problem.

In the long run, AI helps improve wisdom or intelligence.

Machine Learning

Machine learning or MI refers back to the acquisition of a skill or knowledge. Unlike AI, the goal is to boost accuracy relatively than increase the success rate. The concept is quite easy: machine gets data and continues to learn from it.

In different words, the goal of the system is to be taught from the given data with a purpose to maximize the machine performance. Because of this, the system keeps on learning new stuff, which might contain growing self-learning algorithms. In the end, ML is all about acquiring more knowledge.