We hear the terms “AI” and “machine learning” everywhere. They have become predominant with the advancements in technology. More often than not, we notice that they are used interchangeably but did you know that there is a huge difference between these two? Here at robots.net, we’ll try to debunk the mysteries around these concepts. 

Before we dive into what makes the two different, let’s discuss how this sector will perform in the coming years. The Motley Fool did research and found out that by 2020, the AI industry will be valued at $5.05 billion. With this figure, those that are in the industry are reassured that there will be more in the future for them.

Moreover, these statistics have encouraged not only business owners but also machine learning developers who are looking for more ways to innovate in the artificial intelligence sector.

If you are new to this industry, you might be confused between the two and that’s understandable. Oftentimes, we don’t get to learn the fundamentals of AI and ML enough to differentiate the two. Let’s start dissecting each one of them.

What is Artificial Intelligence?

Geeks for Geeks has defined artificial intelligence as the study of how to train computers so they can do things that humans are better at. Simply put, we are teaching machines to act like humans. Many people mistake AI as a system but it is really not. AI is what is implemented in a system so it can stand on its own.

What is Machine Learning?

Machine learning is really just a subset of AI. Rather than creating, machine learning is more of an application and implementation of AI. Here, a computer is given the ability to learn without being monitored by a human. It lets applications and systems modify themselves using the data they gather real-time.

The Difference between AI and ML

Now that we have a general definition of these two terms, let’s look at how different they are from each other by defining the key points that are unique to one of them

Artificial Intelligence

  • Artificial intelligence is a broader topic compared to machine learning. It is generally the application of intelligence to computers so they can function close to how the human brain can.
  • AI is created to focus on increasing the chances of succeeding. It is not developed to solve the accuracy skill of a system.
  • AI is not a system but a concept that can be applied to a system so they can work smarter.
  • The main goal of AI is to solve complex problems by simulating natural intelligence to a machine
  • AI is straightforward and is used to make decisions.
  • AI is created to mimic human reactions. This means that programming is done so the machine will behave specifically according to certain circumstances.
  • AI is programmed to find the best solution.

Machine Learning

  • Machine learning is a subcategory of AI where machines are taught to perform in accordance with what they have experienced in the past. They are given the ability to change their algorithms based on the data they are gathering in real-time.
  • Machine learning is more concerned with accuracy rather than succeeding in record time.
  • The core of machine learning is that it depends on the datasets it receives to become more accurate.
  • Rather than solving problems, machine learning wants the system to improve itself so it can perform better on the task given.
  • Machine learning does not make decisions but it changes its algorithms according to its previous experiences.
  • ML will find a solution. It will not necessarily be the best solution but it will try to find a more accurate solution based on what is given to it so far.

AI and ML Platforms

There are many platforms you can use if you want to start working with AI or ML but we feel like these two below are at the top of the list:

  1. IBM Watson – When it comes to artificial intelligence, IBM has always been at the forefront. It has dedicated a majority of its operations researching this technology for a very long time. They have an in-house AI platform with tools that can be used by both the developers and the business owners. 
  2. Torch – This is an open-source machine learning library that is employed by many big tech companies. It found its success on web platforms and it has extended its service or iOS and Android.


There is no doubt that both of these concepts are important in technology nowadays. With companies looking for more and more ways to innovate their processes, there is no stopping AI and ML. As to which of the two to learn first, it’s really up to you. If you want to understand the bigger picture first, then start with AI. But, if you like to start small and go bigger as you progress, learn ML first.