Computer science is one of the most diverse and complex subjects in the information world. There are multiple topics that are inter-linked with each other which is what causes a great deal of confusion for a layman. Two such topics are Artificial Intelligence (AI) and Machine Learning (ML). Contrary to popular belief, these two branches of computer science are quite different from each other and it is important for us to understand the differences in order to best make use of the two developments.
How are the two terms defined?
The definition of the term “Artificial Intelligence” is fairly simple. The name given to the technology is self-explanatory. “Artificial” is the adjective given to all those things that are man-made with an intention to replicate something that occurs naturally. For example, artificial waves, artificial flowers etc. “Intelligence” is the ability of humans and animals to think and understand things. Artificial Intelligence is, therefore, the ability that is given to computers by man so that they can think, understand and make decisions.
Machine Learning, on the other hand, is the ability of computers and machines to learn and further improve performance from their own experience. This is a branch of AI that gives machines the opportunity to automatically learn on their own without having to be especially programmed.
The main differences
Perhaps the biggest difference between the two terms is that AI is an all-encompassing concept of how machines can perform more and more “human-like” tasks whereas ML is an application of this concept that focuses on only feeding in some data into the machines and letting them learn and improve on their own.
Machine Learning is more aimed at developing a pattern and then using that to handle more advanced experiences while Artificial Intelligence seeks to actively acquire knowledge and/or skill from a particular experience and then apply that in future events.
Moreover, AL is based on the need to find the best, most efficient solution to a particular problem whereas ML is used to only come up with solutions; efficiency is not the main aim.
Artificial Intelligence is a computer program that is built to do “smart” work while Machine Learning is solely a machine that processes data and learns from it. The aim behind AI is to develop computers that can potentially take the place of humans in almost all types of work environments while the aim behind ML is to focus on one task and learn from the data available in order to improve the performance of the particular machine on that particular task only.
In conclusion, Artificial intelligence is a program that has the ability to sense, act, and reason and adapt. Machine Learning, on the other hand, is a series of algorithms that improve overtime as they are exposed to more and more data. Artificial Intelligence helps build wisdom, sensibility and knowing the difference between right and wrong. On the other hand, Machine Learning helps create knowledge.
Regardless of the differences of these two terms, it is very important for us to understand what they mean and how they can both be best implemented in order to take on the information-heavy, computer-dominant, highly competitive future world.
Author | Emily Forbes |
An Entrepreneur, Mother & A passionate tech writer in the technology industry!