Why is Artificial Intelligence and Machine Learning different? [duplicate]

An addition, perhaps this image is more explanatory:

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Matters are taught in different modules because there are many different applications and concepts.

I remember in college I learned this concept, which I believe to some extent:

Artificial Intelligence can be considered any non-human system that performs a certain autonomous task, without the need for intervention of a biological intelligence. Any algorithm that serves some purpose can be considered an artificial intelligence ;

• For example a system that receives X ages and calculates the median of these ages is a type of AI. There is no human intervention for the calculation of the age, except in impute the ages for the machine to make the calculation automatically, to that it is called weak AI.

Machine Learning works as a system that learns what behavior to follow depending on the iterations it has. At first it has a default behavior, but with time, depending on what you enter and the expected output, you can change that behavior or not.

• An example using this great library in js: synaptic.js , specializing in neural networks. In this example, a perceptron algorithm [which is a sub-category of neural networks, which may or may not be a topic of ML depending on the menu of some AI courses] is used to train an algorithm that can solve an XOR alone, in this example used 2 inputs, 3 hidden layers and an output, when we click on start training it shows how many iterations were necessary for the system to learn XOR behavior by itself.

  

Warning: The approach to this post is just one way to treat   subject as wide as artificial intelligence. He must be   understood as objectively and briefly didactic and should not be interpreted   as a closed entry, absolute truth or primary source. O   StackOverflow in Portuguese is a question and answer site   objectives, and it is not part of its scope to elaborate   extensive. For more enlightening questions, chat or   specific documentation of the subject!

Artificial intelligence is a multidisciplinary area involving psychology, philosophy, computation, mathematics, and as reminded by the contribution of Luiz Vieira, also learned in other courses such as the economics course.

Machine learning is one of the subjects learned within the discipline artificial intelligence , which deals with approaches to computational learning algorithms. Learning is one of the known behaviors of the phenomenon of intelligence.

Follow the following reasoning:

  

• 1 - Men Are made of atoms.
  
• 2 - Women are made of atoms.
  
• Conclusion - Men and women are of the same gender as they are made of atoms.
  

This is a small demonstration of the fallacy of composition, which can induce wrong reasoning. This example is not about saying that the topic of the topic is about it, or that different approaches point to it, but a warning that such co-related subjects do not fall into a fallacy. Therefore, from the conceptual semantic point of view, Artificial Intelligence and Machine Learning are different concepts. This is not to say that, depending on the approach, at some point, it may mean the same activity. It all depends on how it is contextualized. I hope I contributed and did not give the impression of being a closed subject.

Finally, I recommend the book " Artificial Intelligence by Peter Norvig and Stuart Russell. In Brazil it is distributed by the Campus publisher. You can find it by Amazon.

You can also find this book in good reputed bookstores.

The view that ML is a subcategory of AI is correct, but to make this understanding clearer, it is important for you to know that when we talk about AI, we are talking about a huge variety of subjects, some of them are: expert systems , machine learning, search algorithms, etc.

In general, the AI disciplines are concerned with presenting an overview of these subjects, promoting an understanding of what exists and possible possibilities, and before this the student / researcher / engineer / programmer can choose which subcategory will investigate better . This can be done through more specific disciplines such as machine learning, which seeks to bring a deeper understanding of techniques such as: Decision Tree-based Learning, Artificial Neural Network, Genetic Algorithms, Clustering.

"So why is it a totally different course?"

This question is independent of how the machine actually works.

"Would you have to see it because it was very complex subjects, or did more or less use of mathematical algorithms?"

There is no computation without algorithms that use math ... The quantity or size is related to the algorithm itself, it depends on what it will do, but both AI will define a whole range of behaviors and interpretations as the ML that will absorb these definitions, will use a reasonable amount of complexity.

I have no doubt that they are closely related terms and that ML is a subcategory of AI.

The difference in my view, since I affirm that ML is sub-category of AI, is that AI is more linked to the cognitive functions inherent to the human being, and that ML uses these concepts to learn and execute. >

In my opinion it is as if AI were the theory and ML the practice.

Then answering your question, "Why Artificial Intelligence and Machine Learning are different matters?" ...

They are not different materials, they are complementary materials ...

Here you can see that ML is a subcategory of AI, of course it is wiki, but by logic we can agree that yes ...

  

    

Machine learning is a sub-field of computer science that has evolved from the study of pattern recognition and the theory of computational learning in artificial intelligence.

  

And here can see you a bit more through the mind of one of the precursors of AI.