The Difference Between AI(Artificial Intelligence) And ML(Machine Learning)

Bernard Marr said:
In short, the best answer is that:
Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”.
And,
Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.

What is Artificial Intelligence?

First coined in 1956 by computer scientist John McCarthy, AI involves machines performing tasks which are characteristic of human intelligence. This spans across industries and includes activities such as planning, recognising objects, and understanding language.
You can understand with the use of the word “Artificial” which refers to something made by a human, i.e. nonnatural thing while “Intelligence” means the ability to understand and think.
Most of the people believe that artificial intelligence is a system, but that is not correct. It is not a system; rather AI is implemented in the system. You can take the meaning of AI with other definitions like, it is the study of providing training to computers to make them do things which humans can do better in the present.
AI aims to increase the chances of success instead of accuracy to simulate natural intelligence for solving complex problems, and it works like a computer program for smart working.

What is Machine Learning?

Computer scientist Arthur Samuel coined the term machine learning as, “the ability to learn without being explicitly programmed.” If AI were to be created without the aspect of machine learning, it would need millions and millions of lines of codes with complex rules, parameters, and decision-trees.
Machine learning is a way of “training” an algorithm so it can learn on its own. This “training” involves sharing huge amounts of data to the algorithm and allowing the algorithm to adjust itself and improve.
It is the branch of artificial intelligence where you study computer algorithms to allow computer programs to improve through the experience automatically.
For example, if you are providing a list of your favourite songs to a machine learning model along with the audio statics like dance, instruments or tempo, etc, it will automate and generate the recommender system to suggest the music in the future you would like to enjoy.
The aim is to increase accuracy, but it does not care about success
参考：
《What Is The Difference Between Artificial Intelligence And Machine Learning?》
《Differences between AI and Machine Learning, and why it matters》
《AI, singularity, and machine learning explained in 5 minutes》