Artificial intelligence and machine learning

 

What is machine learning?

Like most terms in the field of artificial intelligence, machine learning does not have a unique definition.

In simple terms, what machine learning does is use data to answer questions. More formally, it refers to the use of algorithms that distinguish patterns from data and perform tasks without being explicitly programmed.

Moreover, the hallmark of machine learning systems is that they improve performance through experience and data. Or in other words: you study.

What is the relationship between machine learning and artificial intelligence?

Machine learning is part of a group of technologies grouped under the umbrella term "artificial intelligence".

The concepts of artificial intelligence and machine learning often seem to be used interchangeably, but in fact, it is more correct to think of machine learning as a subfield of artificial intelligence.

Artificial intelligence

The term artificial intelligence refers to the ability of a digital computer or computer-controlled robot to perform general tasks associated with intelligent objects. It is a branch of computer science, and a lot of literature defines artificial intelligence as the study and design of intelligent customers, and an intelligent customer is a system that understands its environment and takes positions that increase its chances of success in achieving its mission or team mission.

Since the mid-20th century, scientists have attempted to develop a system capable of performing tasks seen as requiring human intelligence, including electronic games, understanding natural language, diagnosing errors, robotics, and providing expert advice, although computers can be programmed to perform these tasks. And other complex tasks. Significantly, while advances in computer processing speed and memory capacity continue, there are still no programs that can match human flexibility in broader areas or in tasks that require a lot of everyday knowledge.

The difference between Artificial intelligence and machine learning

New technologies indicate these technologies use artificial intelligence technology.

1- Artificial intelligence is a technology that enables machines to simulate human behavior, but machine learning is a subset of artificial intelligence that allows machines to learn automatically from past data without explicit programming.

 2- The goal of artificial intelligence is to create an intelligent, human-like computer system to solve complex problems, but the goal of machine learning is for machines to learn from data so that they can provide accurate output.

3- In artificial intelligence, we allow intelligent systems to perform any task like a human, but in machine learning, we teach machines containing data to perform specific tasks.

 4- Artificial intelligence is the largest technology, machine learning and deep learning are two major subsets of artificial intelligence, and deep learning is a major subset of machine learning.

5- The scope of artificial intelligence is very wide, but the scope of machine learning is limited.

6- Artificial intelligence creates an intelligent system that can perform many complex tasks, and machine learning creates machines that can only perform the specific tasks they have been trained on.

7- The artificial intelligence system is concerned with maximizing the chances of success, but machine learning is concerned with accuracy and patterns.

 8- The main applications of artificial intelligence are Siri, online gaming, intelligent humanoid robots, etc., while the main applications of machine learning are the online recommendation system, Google search algorithms, and automatic Facebook friend tagging suggestions.

 9- Artificial intelligence can be divided into three types based on capabilities, which are weak AI, general AI, and strong AI. Machine learning can also be divided into three basic types, namely, supervised learning, unsupervised learning, and reinforcement learning.

10- Artificial intelligence deals fully with structured, semi-structured and unstructured data, and machine learning deals with structured and semi-structured data.