Artificial Intelligence Versus Machine Learning: Differences You Should Know

Artificial Intelligence Versus Machine Learning: Differences You Should Know

Artificial Intelligence and Machine Learning – these two terms have become increasingly popular among business, consumers and technologists lately, but what do they really mean?

Artificial Intelligence (AI) is a trending topic; and is basically a platform or a solution that seems to be intelligent enough, and can exceed the performance of humans themselves. It can be broadly defined as any machine that imitates human functions or intellectual activities. These activities include, mechanical movements, reasoning, problem solving etc.

Machine Learning, (ML) on the other hand, is a tool (algorithms/statistical models,etc.) that can be used to predict future values based on past data. Machine Learning is a tool for implementing AI. For example, online commerce sites store the purchase history and preferences of a shopper, ML takes a step further in providing personalized product recommendation to the shopper based on previous purchase history and online activity and search data. This, in turn, leads to more sales and hence success of applying machine learning.

Learning Management System is an area where AI can be used to offer personalized courses. With the learning management system (LMS) becoming an increasingly crucial e-learning strategy, it’s very important that you choose the right vendor for it. You could actually end up choosing an LMS that you are overpaying for. So, with hundreds of options to choose from, LMS vendor selection can be a quite daunting task.

Getting back to Artificial Intelligence and Machine Learning, it is interesting to note that these two trending buzzwords are often used interchangeably. But the truth is they are not the same thing. So, let’s see what are the differences between these two which will help us to know these two concepts better.

The Definition Itself

Artificial Intelligence can be defined as the ability of a computer or a machine controlled by a computer to perform tasks as an intelligent living being. They do so in such a manner which is considered to be ‘smart’. Quite Literally. Machine Learning, on the other side, is actually a current application of AI. It has the idea that machines should be capable enough, to access the data themselves and carry out the required task on their own. So, in a nutshell, all machine learning can be counted as AIs, but not all AIs cannot be counted as machine learning.

Recent Developments

Both AI and ML are on the rising portion of the graph, in today’s time and have their respective, developments taking place. Machine Learning has given way to neural networks, which is actually a computer system. It has been designed in such a way, that it classifies and recognizes information just like a human brain does. It works on a theory of probability and data is fed into it. Another application area of AI being much used is called Natural Language Processing (NLP), it deals with the way machines can communicate using human languages. This attempts machines to recognize natural human communications, both written and spoken, and make them learn to respond in the same, natural language. Google Translate is an example where NLP is used to translate texts from one language to another real-time.

A Case of Branding

AI and ML have both come out to be promising technology solutions, which are branded and sold consistently. Industries in every sector are reaping the advantages of these, as they are providing the facility for automation of mundane tasks. Marketers have taken hold of the opportunity to market Machine Learning. AI is a relatively older concept, and there were a few false starts to the AI Revolution. However, with the latest developments in AI and ML you can leverage these technologies to advance your business to the next level.

So, even though we mentioned some of the prime distinguishing factors between AI and MI, we do realize, they are integrated concepts. AI involves platforms that are intelligent. But the catch is, it can include ML solutions, and at the same time can include platforms with no ML at all. So, MI is included in AI, which is also a piece of a much larger puzzle.