Understanding the Difference Between Artificial Intelligence and Machine Learning

Artificial Intelligence has indisputably changed the way businesses are conducted. The emergence of new technologies has triggered companies to bring transitions in their processes and operations. Investing in Artificial intelligence was considered a profligate expenditure that only financial sound companies could afford. But with time, it has become a necessary inclusion in the organization’s fine blueprint and proving to be a game-changer for them.

We often mix up AI and ML thinking that they function on the same functionalities, but in actuality, they are two different principles with a different set of ideologies and utility. Machine Learning is the subset of Artificial Intelligence while there is no denying that both the concepts are the top buzzwords in the digital revolution.

Our good old Siri and Google’s self-driving cars have proven that there is no escaping AI and ML and if you don’t imbibe its spirit in your business, there is a great chance it loses its identity!

It will be good to explore each concept individually and then construe the differences between them.

What is Artificial Intelligence?

In the simplest of terms, when a machine impersonates the behavior of a human, we can understand that Artificial Intelligence is applied. Gartner has unconditionally classified that AI is the biggest game-changer for businesses. Artificial Intelligence is set to become the core of everything that humans interact with for years and years to come.

Earlier we had robots that were programmed mechanically, but with Artificial Intelligence, programmers have successfully been able to embed human-like intelligence, emotions, and behavior in how it is used. Hence, AI is that technology that simulates human behavior. The ability to rationalize and take action about setting goals is what truly defines Artificial intelligence.

AI has become advanced and the primal concepts now are no more under the segregation of AI. For example, machines that calculate basic functionalities or diagnose text using the optimal character recognition no longer comes under the purview of Artificial Intelligence because this has now become an inherent computer functionality.

The versatility of AI in various sectors is undeniable with every industry leader setting benchmarks with AI-based software being inculcated in their businesses.

What is Machine Learning?

If you ask us, what defines a successful business; we will say a lot of things. But the most that matter in today’s time is data management. With the unusual bombardment of data, managing it and making sense out it has become a challenge. Data, when not put to good use, are merely numbers and characters. But, with meanings attached, they become valuable information that can help a business leveraging its power to succeed.

This is where Machine Learning comes into the picture. Machine Learning techniques are employed to explore new trends and decode the hidden information in the data which can be a treasure trove. It is an application and an important component of Artificial Intelligence that provides the system with a natural ability to learn and unlearn without any need for conclusive programming. ML employs a cyclic process that involves observing data, looking for relevant patterns, deduce information based on the data and finally attribute sense in the data to help organizations.

Difference Between Artificial Intelligence and Machine Learning

Now that we have a fairly good idea about what each concept it, it only will help us to etch out differences to see they are not alike.

AI is a budding technology that enables a machine to reproduce human behavior.

Machine Learning is an indispensable constituent of AI that allows the program to learn automatically without the need to program it.

The main goal of AI is to make the machines as smart as a human being.

• Here the goal is to enable the machine to assimilate information and extract important information out of it.
• Here the systems are designed to be intelligent enough to perform tasks like humans.
• In this case, without the need for any additional programming, it expects the system to learn from the data so collected.

Artificial intelligence has a wider span compared because it includes in its orb numerous elements including machine learning and deep learning. On the other hand, the scope of machine learning is not as wide as AI

AI seeks to create intelligent systems that can handle some of the most complex tasks without much human intervention

Machine Learning is about performing those tasks for which the machine has been specifically trained for.

The main applications of AI are Siri, customer support utilizing chatbots, Online gaming, Intelligent humanoid robot and much more.

• Here the main applications of ML are Google search algorithm, FB auto-tagging a friend based on image and online recommender system.
• This includes reasoning and rationalization.
• This includes learning and self-correction with current data.

Future of Artificial Intelligence and Machine Learning

AI and its component ML are going to be a nucleus of the major goals of an organization. In 2020 they are set to become a prioritized portion of the overall strategy. Gartner has already predicted that by 2020, AI will feature among the top 5 business investment fields for about 30% of CIO’s. Both AI and ML are considered to set new benchmarks in the way businesses are conducted.