Over the past few decades, the world has changed in a ton of different ways, but none bigger than when it comes to technology. Things most wouldn’t have imagined to be possible even a few decades ago, are completely possible and widespread today. This is only going to continue to occur as technology is still advancing frequently.

Technology helps us in many different ways from helping or companies be more efficient, helping us organize our personal lives and solving a ton of life’s other problems. For example, there are apps that can control the lights in our homes, tools to monitor distributed Java applications and so much more. It seems that every week there is a new innovation that is continually pushing the industry forward.

Some of the biggest innovations in tech over the last few years have without a doubt been artificial intelligence (AI) and machine learning (ML). They aren’t brand new, so to speak, but are two of the most exciting advancements in the space and have a lot of buzz surrounding them.

But despite what you might believe AI and ML are not actually interchangeable terms for the same thing. In fact, there are actually many distinct differences between the two. With that in mind, this article is going to look at both AI and ML, and the differences between them.

What is Artificial Intelligence?

Artificial intelligence represents the overarching concept of being able to incorporate the intelligence and smart decision-making skills of humans into machines. It is an incredibly large and broad topic and dates back to a conference at Dartmouth College in 1956, which is considered the birthplace of AI.

Artificial intelligence is usually put into two categories, general and narrow or applied. General AI is capable of exhibiting all areas of human intelligence such as problem solving, understanding human language, recognizing things and more. Narrow AI is great and doing certain things, but will be very limited in others.

So a machine that builds a product very fast and efficiently automatically, but can’t do anything else, would be a good example of a narrow AI. As you could imagine, general AI machines are much less common as they are capable of doing so much more and thus are much more difficult to create.

What is Machine Learning?

While many believe machine learning is the same as artificial intelligence, as we mentioned, this is not the case. In fact, machine learning is actually a subset of artificial intelligence. This field of AI is primarily focused on giving machines and computers the ability to learn. Like artificial intelligence, the term “machine learning” was also coined over half a century ago. Artur Samuel coined the term back in 1959 and he defined it as the “field of study that gives computers the ability to learn without being explicitly programmed”.

In order to achieve AI through machine learning, you need to provide a ton of data to the algorithm and allow it to learn about the information being processed. Machine learning is widely used today by a variety of different companies such as Facebook, Google and Netflix.

The idea of machine learning itself is based on something called neural networks. The idea of neural networks is quite complicated, but they are essentially networks that are built to train and/or learn. Simply put, neural networks help to allow computers to mimic the brains of humans without the bias and with increased speed and accuracy. Once perfected, the network will help the machine to learn and improve itself without any sort of intervention from humans.

The Differences Between AI and ML

Just to wrap up and conclude the article, we thought we would review and clearly list some of the distinct differences between AI and ML that we touched on throughout this article.

The differences between AI and ML include:

  • Machine learning is actually a subset of artificial intelligence and is also a way to achieve artificial intelligence.
  • Artificial intelligence is a much more broad and general concept than machine learning.
  • AI as a technology allows a system to demonstrate human-like intelligence, and machine learning uses mathematical models and data to make decisions and the more data included, the better the machine learning will be. As a result, machine learning doesn’t have any “real” intelligence, so to speak.

In conclusion, hopefully, this article has helped you understand a little bit more about artificial intelligence and machine learning, and the differences between the two of them. They will likely continue to grow and be used in a much wider fashion and be adopted by many more product or companies. While they have some things in common, they are not the same and recognizing the difference is important if you ever want to use these in your personal lives or for your business.