Web technologies have revolutionized the way we used to think and imagine. People have always feared to be replaced by the so called machines as they have the potential to improve and innovate in ways we cannot even imagine. The looming technological revolution is slowly taking over our jobs and the time is not far off when they’ll soon wipe up off from the face of the earth. What started truly as a fictional phenomenon in movies has become one of the hottest buzzwords of today. Yes, we are talking about Artificial Intelligence, or simply called as AI. The technological progress alone is evident of the fact that AI is the future and the next step of human evolution.
The term AI has been around for a while. You must have seen it in Sci-Fi movies like “The Matrix”, “Eagle Eye”, “The Terminator”, etc. Well, you’re not going to end up fighting those scary robots though. Unlike movies, AI will not replace humans, at least not anytime soon, nor will it fight with us. Instead, AI is just a simulation of human intelligence driven by machines and integrated into human cognition to carry out tasks in a ‘smart’ way. In a way, AI is making humans super smart, not the machines. Then there’s another term that is often used interchangeably with AI – machine learning. So, we present an unbiased comparison to help you better understand the difference between the two.
What is Artificial Intelligence?
Artificial Intelligence, or commonly referred to as “AI”, is a science of creating machines to accomplish tasks or solve problems that are too complicated for the human brain to process all by itself. AI is your smartphone, computer solving complex problems, a robot doing human work, in fact, AI is all of these things and much more. AI has transformed the world in exciting and amazing ways. The term didn’t even exist until the 1950’s, but thanks to John McCarthy, AI has become one of the major breakthroughs the world has ever witnessed. Simply put, AI is the idea of making machines think like humans.
What is Machine Learning?
Machine Learning is one of the most advanced scientific fields of today’s technology-advanced era and a way of achieving artificial intelligence. It is the computational study of algorithms based on automated learning approaches that underlie learning in both humans and machines. It is a subset of AI and cognitive science that is based on learning algorithms that are fundamentally consistent with knowledge of the human cognitive architecture. Simply put, machine learning gives machines the ability to think and learn in more human ways without being explicitly programmed.
Difference between Machine Learning and AI
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Meaning of Machine Learning and AI
Artificial Intelligence, or simply called as AI, comprises of two words artificial and intelligence. Artificial means something that is made by human or non natural being and intelligence means the ability to think or understand. AI falls under the category of computer science which simply means augmenting the capability of machines in contrast with the human intelligence to accomplish a task or solve a problem. Machine Learning is a modern-day application of AI describes as a way to achieve AI which provides machines the ability to learn automatically without being explicitly programmed.
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Technology involved in Machine Learning verses AI
AI refers to the technology designed to surpass the abilities of machines to think like humans, mostly in computational systems. AI is simply human intelligence integrated into machines in order to accomplish tasks in a way that is considered “smart”. It’s the ability of a machine or a computer program to think, learn, and understand in order to make them smart like humans. Machine learning, on the other hand, is based on the idea that systems can act and learn from data that is either unstructured or unlabeled. It simply is the ability to give computers the ability to learn without being programmed.
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Function of Machine Learning and AI
The term AI is applied to when a machine mimics human cognitive functions for thinking, problem solving, memory, perception, and decision making. The primary goal of artificial intelligence is to program machines to carry out tasks in more human ways. AI is fundamentally classified into two groups – general and applied. General AI in intelligence exhibited by machines to perform any task that a human can, whereas Applied AI is the use of AI to enhance and extend software applications. The key to teaching computers to think and understand like we do is machine learning. The whole system is based on probability and based on the data fed, it’s able to take decisions with a certain degree of certainty.
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Applications of Machine Learning and AI
The most common applications of AI in business and consumer spaces is Google’s DeepMind, the latest program from Google’s artificial intelligence group, and Apple’s Siri. The basic example of AI is the Tic-Tac-Toe AI player. AI is used in computer-aided digital images to highlight conspicuous sections of the body to detect tumors. AI technology is used to develop many fields and sectors including finance, education, healthcare, aviation, media, marketing, and more. Machine learning is used in a wide range of applications including medical industry, speech recognition, optical character recognition, email filtering, web security, etc.
Machine Learning vs. Artificial Intelligence: Comparison Chart
Summary of Machine Learning verses Artificial Intelligence
In a nutshell, AI is a simulation of natural intelligence integrated with human cognition into machines or computer programs to carry out simple to complex tasks in smart ways. Machine learning is an application of artificial intelligence that gives computers the ability to learn and understand things like we do without being explicitly programmed. Both the terms are often confused with each other, but they are not quite the same thing. AI is something that is capable of challenging human cognition, something that hasn’t yet affected by the technological evolution, whereas machine learning is an incredible form of artificial intelligence which is based on the idea of supervised learning.