Artificial Intelligence (AI) and Machine Learning (ML) are often used interchangeably because there is a lot of confusion in public. Some companies take advantage of the confusion and make a false claim on their products to work on Artificial Intelligence when in reality, it is nothing but Machine Learning. These two terms used synonymously in some cases while discrete in the others. The situation entirely depends on the marketing strategy of the company.
A recent report on the issue focusing on misleading claims made by companies in order to attract customers. According to the report, around 40% of European startups that claimed to use Artificial Intelligence don’t use the technology at all.
Nevertheless, this article will take you through the difference between AI and ML so that you can differ between the two as well as fall out of the misleading traps created by companies. Here’s all you need to know about it-
What is Machine Learning?
Have you heard about the term computer algorithm?
Machine Learning is nothing but an extension of the computer algorithm to improve computer programs and use experience. We can call Machine Learning as a part of Artificial Intelligence. Confused already? Let’s dig into it more –
We all know that machines work on a specific set of algorithms, which makes the process faster and easier for users. It is based on small to large data sets, analyzing the data, and finding common parameters to explore limitations between the two. For example, you might have noticed a song application to recommend your songs based on your previous playlist. It is because of the automation and recommender system of the application which analyzes data and finds similar to your choices. That’s exactly what Netflix or Spotify does.
To put it in simpler words, then Machine Learning is a program where you put large data set along with its description. The program assists in analyzing the data and exploring common sets to create a fast and effective system. Based on this, we can classify Machine Learning into two types, viz. Supervised learning and unsupervised learning.
Supervised learning is working on analyzing different relationships and dependencies between the target prediction outcome and input features. Thus, Netflix and Spotify is nothing but an example of Supervised Machine Learning, where the output is based on your repetitive pattern of inputs.
On the other hand, pattern detection and descriptive modeling are the principles used for unsupervised learning. This type of learning does not classify the data based on labels and treat them separately.
In short, Machine Learning is all about rendering algorithms and simplifying the system. The sub-branches of Machine Learning, viz, deep thinking and neural network are intriguing and also compared with the human brain.
Now, let’s discuss Artificial Intelligence –
What is Artificial Intelligence?
Artificial Intelligence is the science and engineering of making computers to behave in a way that only requires human intelligence.
The above statement might seem vague and broad in spectrum. But it shows a wide scope in the field. Years from now, a simple automated chess program was also considered to be a form of intelligence because only a human brain can play chess. Until recently, a chess program is outdated because it can be found on every mobile operating system.
Today, we know Artificial Intelligence differently. It is about human-Artificial Intelligence communication. For example, Siri, Alexa, Google Home show technological advances whereby gadgets are able to communicate with humans. So, we can call AI as a study of training computers to do things which in present only humans can do better. While Machine Learning focuses on learning new from the acquired data, Artificial Intelligence is based on decision making. The goal of AI is to solve complex problems by simulating human intelligence.
Thus, it leads to developing a system to mimic human responses in different circumstances. While Machine Learning leads to knowledge, Artificial Intelligence leads to wisdom. And we know how discrete knowledge and wisdom are!
Now, the big question –
Why Do Companies Use The Two Terms Interchangeably?
The inception of Artificial Intelligence began in the year in 1956, and since, then there has been a confusion between Machine Learning and AI itself. For example, IBM developed a supercomputer DeepBlue that actually worked on Artificial Intelligence, but the company claimed otherwise. DeepBlue performed such tasks, including facial recognition, which were impossible to function without AI.
At the same time, predictive data analytics, data recognition, and Machine Learning started gaining certain momentum. Companies began to focus on deep thinking and neural network to advertise their products. The era was more of Machine Learning. Nevertheless, in recent times, AI has been on a great hike, and we can call our time with Siri and Alexa to be of artificial intelligence. The companies in order to broadcast their products offer different schemes which are falsely based on AI. For example, high-end games, and supernatural portrayal of AI. This leads to mistrust and confusion among the public.
The companies in order to gain their short-term goals hire humans to work on the loopholes created by their so-called AI software. The entire game is to earn profit by misleading the public. Hence, you can see these two terms used synonymously in different cases.
Machine Learning and Artificial Intelligence are two broad terms.
For instance, Machine Learning applications can play you music, find music according to your mood, read your text and predict whether someone is congratulating you or yelling at you. On the other hand, Artificial Intelligence mimics the human brain. It is based on acting like a human in different circumstances. It is about understanding human communication and reacting in a similar, natural language.