How artificial intelligence differs from machine learning
Often, the concepts of “artificial intelligence” and “machine learning” are equated. However, machine learning is actually a way to create and train artificial intelligence.
To understand the difference, let’s present the following course of action:
1) The programmer creates a program that is capable of learning, but the program still does not know how to accomplish a certain task.
2) The programmer then trains the program using machine learning techniques. These can be, for example, neural networks or genetic algorithms.
3) After training, the program acquires artificial intelligence. We can also say that the program itself becomes an artificial intelligence.
Machine learning is the only know way to create artificial intelligence today.
When someone says that they developed artificial intelligence, they utilized machine learning to create it. Meanwhile, if someone says that they are using machine learning, they are, in fact, using artificial intelligence, since “learning” itself cannot perform any tasks.
Yet, artificial intelligence isn’t just about machine learning. AI requires computing power, data, and other programs and technologies. Therefore, there these two terms are not equivalent.
To quickly create AI powered by machine learning, one can rent computing power in the cloud. Many cloud platforms have a service for rapid application development based on machine learning.
Perhaps in the future there will be other ways to create artificial intelligence. For example, people will learn to copy the human brain and imitate biological processes. In this case, machine learning may disappear, but artificial intelligence is not going anywhere and may become even more advanced.
