Both Machine learning and artificial intelligence are common terms used in the field of computer science. However, there are some differences between the two. In this article, we are going to talk about the differences that set the two fields apart. The differences will help you get a better understanding of the two fields. Read on to find out more.
As 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 to the ability of humans to think or understand.
First of all, it’s important to keep in mind that AI is not a system. Instead, in refers to something that you implement in a system. Although there are many definitions of AI, one of them is very important. AI is the study that helps train computers in order 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 allows a machine to learn on its own and no programming is involved. In other words, the system learns and improves automatically with time.
So, you can make a program that learns from its experience with the passage of time. Let’s now take a look at some of the primary differences between the two terms.
AI (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 primary purpose of an AI based system is to increase the likelihood of success, not accuracy. So, it doesn’t revolve around increasing the accuracy.
It involves a computer application that does work in a smart way like humans. The goal is to boost the natural intelligence in order to solve a lot of complex problems.
It’s about decision making, which leads to the development of a system that mimics humans to react in certain circumstances. In fact, it looks for the optimal solution to the given problem.
In the end, AI helps improve wisdom or intelligence.
Machine learning or MI refers to the acquisition of a skill or knowledge. Unlike AI, the goal is to boost accuracy rather than boost the success rate. The concept is quite simple: machine gets data and continues to learn from it.
In other words, the goal of the system is to learn from the given data in order to maximize the machine performance. As a result, the system keeps on learning new stuff, which may involve developing self-learning algorithms. In the end, ML is all about acquiring more knowledge.
Long story short, this was an introduction to MI and AI. We also discussed the primary points of differences between the two fields. If you are interested in these fields, you can ask experts for more knowledge