Clearing the Confusion: AI vs Machine Learning vs Deep Learning Differences
Raise your hand if you’ve been caught in the confusion of differentiating artificial intelligence (AI) vs machine learning (ML) vs deep learning (DL)…
Bring down your hand, buddy, we can’t see it!
Although the three terminologies are usually used interchangeably, they do not quite refer to the same things.
Andrey Bulezyuk, who is a German-based computer expert and has more than five years of experience in teaching people how artificial intelligence systems work, says that “practitioners in this field can clearly articulate the differences between the three closely-related terms.”
Therefore, is there a difference between artificial intelligence, machine learning, and deep learning?
Here is an image that attempts to visualize the distinction between them:
As you can see on the above image of three concentric circles, DL is a subset of ML, which is also a subset of AI.
So, AI is the all-encompassing concept that initially erupted, then followed by ML that thrived later, and lastly DL that is promising to escalate the advances of AI to another level.
Let’s dig deeper so that you can understand which is better for your specific use case: artificial intelligence, machine learning, or deep learning.
As the name suggests, artificial intelligence can be loosely interpreted to mean incorporating human intelligence to machines.
Artificial intelligence is the broader concept that consists of everything from Good Old-Fashioned AI (GOFAI) all the way to futuristic technologies such as deep learning.
Whenever a machine completes tasks based on a set of stipulated rules that solve problems (algorithms), such an “intelligent” behavior is what is called artificial intelligence.
For example, such machines can move and manipulate objects, recognize whether someone has raised the hands, or solve other problems.
AI-powered machines are usually classified into two groups — general and narrow. The general artificial intelligence AI machines can intelligently solve problems, like the ones mentioned above.
The narrow intelligence AI machines can perform specific tasks very well, sometimes better than humans — though they are limited in scope.
The technology used for classifying images on Pinterest is an example of narrow AI.
As the name suggests, machine learning can be loosely interpreted to mean empowering computer systems with the ability to “learn”.
