Artificial Intelligence (AI) and Machine Learning (ML) are the latest and hot buzzwords these days. Sometimes, these terms are also used interchangeably. The perception can lead to some confusion, but these are not the same thing. Hence, we thought it would be worth explaining the difference between ML and AI.
Let us get started!
An Overview of Artificial Intelligence and Machine Learning
Before moving further, understand these terms first. Artificial Intelligence or AI consists of two words – Artificial and Intelligence. Here, Artificial means something made by a human or a non-natural thing. While Intelligence refers to the ability to think or understand. There is a misconception about AI that it is a system but in reality, it is not. AI is implemented in the systems.
In simple words: AI is nothing but the study of how to train systems or computers so that they can do things better and quicker than humans. Also, it is an intelligence where all capabilities can be added to the machine that humans hold.
When we talk about Machine Learning, it is the learning wherein machines can learn on their own without the help of any program. ML is an application of AI. It is designed to provide the system with the ability to learn and improve automatically from experience. Here, programs can be generated by integrating input and output to that particular program.
Understand ML with the following definition given by the Machine Learning pioneer and computer scientist Tom M. Mitchell: Machine learning is the study of computer algorithms that allow computer programs to automatically improve through experience.
Artificial Intelligence vs. Machine Learning
To help you understand these two innovations better, we have tabulated the major differences of these terms below. Have a look:
|Particular||Artificial Intelligence||Machine Learning|
|Meaning||AI is the intelligence in which the intelligence is the clear acquisition of the knowledge. Here, intelligence is mentioned as the ability to gain and apply that knowledge||ML is the acquisition of skills or knowledge|
|Aim||The aim of AI is to increase the success rate, not the accuracy||ML is all about focusing on the accuracy, not on the success|
|Other Differences||· It acts like a computer program that works smartly
· The goal of AI is to stimulate natural intelligence to solve even the most complex task
· AI is all about decision-making
· AI develops a system to copy human to respond
· AI focuses on finding the optimal solutions
· AI leads to wisdom or intelligence
|· It is a simple concept in which machine takes data and learn from it
· The goal of ML is to take data and learn from it on a certain task to maximize the performance of the machine
· ML is all about allowing systems to learn new things from data
· ML creates self-learning algorithms
· ML focuses on solutions no matter whether they are optimal or not
· ML leads to knowledge
To conclude this, we can say that ML uses the experiences to find the patterns it learned. While AI uses the experiences to obtain skills or knowledge and to know how to apply that acquired knowledge or skill for new environments. Both ML and AI can have valuable business applications. But, in the present scenario, ML is ahead for helping businesses solve critical problems.
We hope that there is no confusion left and concepts are clear now. In case of any query or question or to know where and how to pursue these new-age technologies, connect with us on +91-8448446609 or 011-43334444, or share your queries with us at firstname.lastname@example.org.