What’s the Difference Between Artificial Intelligence and Machine Learning

With the development of new technologies, many people wonder if there is any difference between artificial intelligence and machine learning.

Though they may look similar, artificial intelligence and machine learning are different. Both have unique features and capabilities.

This article will explore the difference between the two using several definitions and examples.

First, we will define each.

What Is Artificial Intelligence?

Artificial intelligence is a computer science technique that attempts to mimic human intelligence by simulating its underlying cognitive processes.

Artificial intelligence is often used in the context of intelligent machines. It is also frequently used for more general purposes, including the following:

•         Voice assistant engines in mobile devices
•         Computer gaming
•         Virtual assistants in search engines
•         Robotics, where it can perform piece picking

Artificial intelligence originally referred to the concepts known as logic and learning theory. Scientists intended to use it to explain how humans think at a high level of abstraction.

AI generally incorporates study algorithms. These algorithms are what enable the system to execute tasks predictively.

Artificial intelligence can be split into three different levels:

1.       Strong AI, the pinnacle of AI advancements, is the closest to accurate artificial intelligence.
2.       Weak AI is the artificial intelligence that we interact with most often.
3.       General AI is artificial intelligence whose capabilities fall between strong and weak AI.

What Is Machine Learning?

Machine learning is a branch of computer science that provides predictive modeling and pattern recognition tools.

Machine learning typically proceeds by formulating an object to be solved and developing computer algorithms to predict the desired outcome.

In general, it has its roots in AI, but it has become more specific over time. It works through data that has been extracted from a specific task. Typically, machine learning predicts the next move through a set of previously entered moves into your system. It is a subset of artificial intelligence, but it requires more human intervention to exist.

Examples of machine learning models include the following:

1.       Search filters
2.       Social network predictive systems
3.       Spam trays in communication networks

Machine Learning in Social Networks

In social networks like Facebook, machine learning will help with recommendations of friends or media that you may like. It is based on the previously watched media or friends you previously followed.

Machine Learning in Product Recommendation

In websites like YouTube, Netflix, and Amazon, machine learning is used for new recommendations based on what you viewed before. If, for example, you viewed a 2020 action movie on Netflix, you are more likely to get a recommendation of other action movies produced within the same period.

Machine Learning in Email Filtering

Machine learning will automatically filter out emails you previously flagged as spam.

Differences Between Artificial Intelligence and Machine Learning

The following are some of the differences between artificial intelligence and machine learning:

• Machine learning works based on previous experience to predict the next move. Even if you’ve never played a specific game, machine learning will still be able to predict your next moves in that game based on previous experiences of other users who have played it.
• For artificial intelligence, it will depend on machine learning to learn the specific rules of that game. But you can use machine learning in any situation based on previous experiences.
• In artificial intelligence, a user can program a machine to mimic a human’s behaviors. In machine learning, a user can only automate a machine to perform human tasks based on previous data sets. Artificial intelligence is more simulated than machine learning.
• As seen from above, AI is more simulated. Therefore, it can be a perfect solution to complex problems at work or home. The machine model will learn about the nature of the work and the problem at hand with a database collected with the help of machine learning.
• With artificial intelligence, you can develop complete results, while in machine learning, you are limited because learning works with available data.
• Another difference is applications. Artificial intelligence is used in machines that solve many problems like Siri or Google Assistant voice engines.
• On the other hand, assisted learning is used in search engines, email filters, or social networks. Machine learning is an alternative, while artificial intelligence is necessary for technology.

Artificial Intelligence vs. Machine Learning Which Is the Best?

Machine learning is a data-driven field, while artificial intelligence is simulated.

Using this definition, we can conclude that artificial intelligence is more helpful, and it’s something you should invest in if you are looking to solve problems in your business or personal life. It gives better performance, and we could see it surpass human reasoning with proper advancements.

Read also: How To Boost Your Data Science Skills?