What is the difference between artificial intelligence (AI) and machine learning (ML)?

ML is subset of AI. You can refer to the following diagram & their definition differences. There are many more of such diagrams when you do a Google search.

Dear Modestus Okwu ,

See the link, please.

https://medium.com/iotforall/the-difference-between-artificial-intelligence-machine-learning-and-deep-learning-3aa67bff5991

https://www.youtube.com/watch?v=q7bKMHdxtPU

Regards, Shafagat

AI involves machines that can perform tasks that are characteristic of human intelligence. While this is rather general, it includes things like planning, understanding language, recognizing objects and sounds, learning, and problem solving.

Machine Learning: A type of AI that can include but isn’t limited to neural networks and deep learning. Generally, it is the ability for a computer to output or do something that it wasn’t programmed to do.

Dr. Shafagat Mahmudova,

Thank you for your time, prompt response and interesting links. The information provided are very useful.

Regards,

Modestus.

Dear A. K. Roy,

Thank you for your timely response and vital information.

Regards,

Modestus.

thanks for recommending my answer@

• Syed Ismyl Mahmood Rizvi
• Modestus Okwu
• Yehya A. Salih
• Alexey K. Kovalev

What is the difference between artificial intelligence (AI) and machine learning (ML)?

ML is subset of AI. You can refer to the following diagram & their definition differences. There are many more of such diagrams when you do a Google search.

thanks for recommending my answer@

• Syed Ismyl Mahmood Rizvi
• Modestus Okwu
• Yehya A. Salih
• Alexey K. Kovalev

Thank you Han Ping Fung for the information you provided. It is straight to the point. The diagram definition is detailed enough for a lay man to comprehend.

Regards,

Modestus.

Thank you very much Ajit kumar Roy for your willingness and interest in this discussion.

Regards,'

Modestus.

Speaking in general, Machine Learning does not replace all Artificial Intelligence (AI), it only becomes one of its strongest part. AI also includes parts of expert systems (especially fuzzy ES), genetic algorithms, etc. So, machine learning should be considered as part of AI.

AI can provide answers to WHY, while ML will not be able to answer it.

Dear N. Allahverdi,

Thank you for your time and detailed response.

Regards,

Modestus.

Dear Supriana,

Thank you for your prompt and brief response. Your comment is noted with delight.

Regards,

Modestus.

Artificial intelligence is an ability of a machine to understand, analyse and make decisions.

Machine learning is one the technique used to teach machine a skill of understanding and analysing.

Thank you for your prompt response to the question raised. Am glad you provided a good definition of AI and ML.

Regards,

Modestus.

Machine learning is a particular approach to artificial intelligence.

AI is field of study with the goal of creating machines that exhibit intelligence while ML is a sub-field of AI, whose focus is to use data to train computer algorithms to perform tasks that typically cannot be done (or very difficult to accomplish) through hard wiring the logic into a program.

Deep learning is another term used which is actually a class of machine learning algorithms.

Big Think: What's the difference between A.I., machine learning, and robotics?.

http://bigthink.com/mike-colagrossi/whats-the-difference-between-ai-machine-learning-and-robotics

Roshan Koju,

Thank you for your response and for clearly stating the difference between artificial intelligence (AI) and machine learning (ML). Your information is well noted with delight.

Regards,

Modestus.

Dear I. B. Kattubadi,

Thank you for the interesting link you forwarded, highlighting the difference between AI, ML and Robotics. It is very useful.

Regards,

Modestus.

Here are 20 subtopics from 58 articles from Web of Science with words

( artificial intelligence machine learning ) in their titles . Each topic is represented by 20 words and 20 phrases through which it is discussed in these articles. In addition for each topic there are qotes from 2 documents in which it greatly represented.

We will be grateful for the feedback.

AI stands for artificial intelligence, where intelligence is defined as the ability to acquire and apply knowledge.

ML stands for machine learning where learning is defined as the acquisition of knowledge or skills through experience, study, or by being taught.

Let me illustrate the difference with a simple example:

Imagine we want to create artificial ants who can crawl around in two dimensional space. However, there are dangers in this world: if a ant encounters a poisonous area, it will die. If there are no poison in ant’s proximity, the ant will live.

How can we teach ants to avoid poisonous areas, so that these ants can live as long as they wish? Let’s give our ants a simple instruction set that they can follow; they can move freely in two dimensional space one unit at a time. Our first attempt is to allow ants to crawl around by generating random instructions. Then we tweak these ants and let them crawl around the world again. We repeat this until ants successfully avoid the poisonous areas in the world. This is a holistic machine learning way to approach the problem. We make ants to fit in configuration by using some arbitrary rule. This works because in each iteration we prune away a set of non-fitting ants. Eventually, we are pushed towards more fitting ants.

But what if we change the location of poisonous areas, what do you think will happen? Ants would undergo a huge crisis because they couldn’t survive in the world anymore – they couldn’t simply know where the poisonous areas are and therefore would not be able to avoid them. But why this happens, and could we do any better? Could ants somehow know where the areas are and adapt their behavior to make them more successful? This is where artificial intelligence comes into play. We need a way to give ants this information, give them knowledge of the environment. Our ants need a way to sense the world. Until this, they have been living in completely darkness, without any way to perceive the world around them. For example, we can let ants to leave a short trail which other ants can sense. Then we can make ants to follow this trail and if they cannot sense a trail, they just crawl around randomly. Now, if there are multiple ants, most of them will hit the poisonous areas and die. But there are also ants who won’t die and therefore crawl in a non-poisonous areas – they will leave a trail! Other ants can follow this trail blindly and always know that they will live. This works because ants can receive some information of their surroundings. They can’t perceive the poisonous areas (they don’t even know what poison is), but they can avoid them even in completely new environments without any special learning.

These two approaches are quite different.

• The machine learning way tries to find a pattern which ants can follow and succeed. But it doesn’t give ants a change to make local decisions.
• Artificial intelligence way is to let ants to make local decisions to be successful as a whole. In nature, we can find many similarities to this kind of artificial intelligence way to solve problems.

Hope that draws clear distinction between AI and ML.

Source: https://www.quora.com/What-are-the-main-differences-between-artificial-intelligence-and-machine-learning-Is-machine-learning-a-part-of-artificial-intelligence

Thank you Nikisha Jariwala .

The information is detailed and useful.

Regards,

Modestus.

AI is the study of how to train the computers so that computers can do things which at present human can do better.

Machine Learning is said to learn from experience E w.r.t some class of task T and a performance measure P if learners performance at the task in the class as measured by P improves with experiences.”

Dear Ajit Kumar Roy,

Thank you very much for your valuable contribution.

Regards,

Modestus.

AI includes the following: Expert systems, Fuzzy Logic and Neural network.

ML belongs to AI domain : ML is a domain which is concerned with building systems that analyse, learn and recognize signals in order to mimic humans.

Thank you very much Mohamed Hassine.

Regards,

Modestus.

I think that the main characterization of AI is dependent on the characterization of the reasoning. I agree that are two main characteristics of reasoning : heuristic and procedural. The heuristic part scope is this one concerning the capacity of human being to discover concepts (notions) and to do their representation. The procedural part is that one dealing with the capacity of the human being to conceive and to execute procedure. The AI try to implement on machine the human reasoning but, in my opinion, only the procedural part is more or less well implemented. The heuristic part is still a great problem to be analyse. There is another part of human behavior which is not very well captured on the machine : emotional part

i.e. all belonging to the psychology and self conscience.

Is the machine conscientious of what it does ? They are still many interrogations as :

What is the "natural intelligence" ?

What is the self conscience ?

The deep learning is only a part of the whole which must be the AI.

Dear Anca C. Pascu,

Thank you very much for your response and vital information.

Regards,

Modestus.

The ability of a machine to classify data, speech, images, tweets etc. on the basic of their intelligence with the help of "piece of program" is known as artificial intelligence. This piece of computer program along with sufficient data helps machine to learn and develop intelligence. Hence, the learning approach is known as machine learning and the intelligence is artificial intelligence.

Thank you for your feedback Asif Iqbal.

Regards,

Modestus.

Dear Dr. Modestus Okwu ,

The entire discussion was informative.

Regards,

Er.Kiran K John

General and basicQuestion

Thank you Kiran K. John. Quite an interesting discussion.

In the name of God,

Perhaps, ML ⊆ AI.