[ Science ]

The Main Differences between AI and Machine Learning

It is very easy to confuse the two terms, and you will often read or hear someone use them interchangeably. Are they the same thing, or completely different? Is one a subset of the other? Let us dive in and analyze the biggest differences between AI and machine learning.

What is AI?

AI stands for artificial intelligence. If we disregard philosophical debates and stick to computer science, AI is a system’s ability to correctly interpret and learn from data, thereby being able to complete its tasks and goals.

The usual goals for AI include reasoning, natural language processing, learning, planning, and others. AI has applications in video games, healthcare, military, and economics; it is also used to calculate complex problems, like the odds of a sports game, or for predicting the outcome of a gambling game in online casinos like InPlay Casino. It is the attempt to make human-like intelligence in a machine. There have been countless novels, movies, and other portrayals of AI in fiction that open a large number of ethical and theoretical questions about the future of AI and humanity.

What Is Machine Learning?

Machine learning is the study of algorithms that a system uses in order to solve a task without any input or instructions from a human being. It is used in sorting, data mining, anomaly detection, and other fields. Its limits lie in the potential lack of data, bias during the input, wrong tools, and so on.

Machine learning can be supervised, semi-supervised, and unsupervised. It is the act of computers getting things done without being told to. You can find machine learning in the ability of systems to recognize images, speech patterns, etc.

What Is the Connection?

Machine learning is often regarded as a subset of AI. In other words, AI must contain machine learning as a part of its processes, whereas machine learning doesn’t need AI in order to remain machine learning. Interestingly enough, there is one more level – deep learning is the subset of machine learning.

Machine learning, as the name implies, gives AI the ability to learn from experiences and, subsequently, devise a plan to make future decisions based on that experience.

Why the Confusion?

Basically, it has to do with generating hype and promoting a brand. Every time a machine does something without being instructed to, people consider it AI. It is somewhat understandable – more exposure means more time and money to work on the development of new technology.

However, now you know that machine learning is a subset of AI that provides it with the ability to learn things, while there is still a lot of grey area concerning the proper definition of AI itself. Machine learning is pretty clearly defined, while what AI is and what it will become remains to be seen.