Human endeavor has been to make machines think and act like humans. Intelligence provided to the machines is referred to as Artificial Intelligence. Using Artificial Intelligence, machines are to be developed to perform tasks requiring human intelligence.

When computers were invented, it became possible for humans to assign tasks to machines so that they could repeat a set of instructions without getting tired and without making any mistakes. In today’s world, there are many single tasks that computers can master and perform without any human interference. For example, a telecom company uses a computer to keep track of all the usages made by its customers. The computer keeps track of every kind of voice, text, and data usage made by the customers and reports them as Call Detail Records (CDRs). Nowadays, they are called XDRs as mobile phones are used for many purposes other than making calls. However, in recording XDRs, the computer follows predefined instructions. It is not thinking anything.

A logical extension was for computers to decide whether to allow customers to continue incurring telephone charges based on their entitlements. So, Intelligent Networks (IN) were invented, which are computers that enable customers to use telephone networks only if they have entitlements. Here again, the computers follow instructions to determine whether the customers have entitlements and allow or disallow usage of the telecom network. These computers also do not think.

When telephony customers make long-distance calls (for example, from Bengaluru to New York), the telephone company can route the call through various routes. For example, the call could be routed through London, Singapore, Tokyo, Gabon, or Amsterdam. The computer needs to decide the route based on many factors, such as which route would result in the best quality call, what would be the cheapest route, from which of the telecom partners en route it is easiest to get payments, etc. For the same, the computers are fed many past call data and the results of those experiences. Based on this input data, the computer can decide, on its own, the best route to use for the current call. Here, the computer has started to think.

The challenge of routing calls, known as the Least Cost Routing problem, was initially solved by computers using matrices. However, with the advent of Machine Learning, computers can now analyze millions of past routing decisions and determine the best route based on various factors, including customer preferences and network conditions. This is a prime example of how computers are now capable of making decisions.

Machine Learning, a subset of Artificial Intelligence, enables computers to learn patterns from data and make inferences. However, these inferences are limited to the intelligence in the data and the patterns recognized by the computers. It's important to note that human intervention is still necessary when computers make incorrect decisions based on machine learning.

Dear Wisam Mohammed Abed Alqaraghuli ,

Machine learning is an application of AI. It's the process of using mathematical models of data to help a computer learn without direct instruction. This enables a computer system to continue learning and improving on its own, based on experience.

https://azure.microsoft.com/en-us/resources/cloud-computing-dictionary/artificial-intelligence-vs-machine-learning#:~:text=Machine%20learning%20is%20an%20application,its%20own%2C%20based%20on%20experience.

Regards,

Shafagat

Artificial intelligence (AI) is a broad field encompassing any intelligent behavior exhibited by machines. Machine learning (ML) is a specific technique under the AI umbrella that allows machines to learn from data.

It's a good question, and AI and Machine Learning are related but far from being the same thing:

machine learning is a key technique within the broader field of artificial intelligence, enabling AI systems to learn and adapt from data to perform tasks more effectively.

Let's imagine We're teaching a dog a trick, and We show the dog exactly what to do, again and again.

Machine learning is more like leaving a pile of treats and a clicker to the dog, and the dog figures out that clicking the clicker gets a treat, and eventually connects that to shaking its paw, that is learning through experience, and it is what machine learning algorithms do.

AI is the whole project, and its goal is to create intelligent machines that can learn and solve problems like humans. Machine learning and deep learning are powerful tools to achieve that artificial intelligence.

Ps, Any suggestion I'll be grateful!

Machine learning is the branch of AI.