Are Artificial Intelligence (AI) and Machine Learning (ML) the same thing? Many people confuse these two concepts, using one instead of another and vice versa. Unfortunately, companies mislead their customers by promising AI instead of ML or some unrealistic combination of the two.
In the realm of big data, AI and ML are often used interchangeably. With all the hype going on about these two ideas, it’s easy to get lost and fail to see the difference. For example, just because you use a certain algorithm to calculate information, it doesn’t mean that you have AI or ML at work. What does? Let’s start with the basics.
What Is An Algorithm?
An algorithm is simply a set of actions to be followed in order to get to a solution. When it comes to ML, the algorithms involve taking data and performing calculations to find an answer. The complexity of these calculations differs depending on the task. The best algorithm allows you to get the right answer in the most efficient manner.
If an algorithm works longer than a human does, it’s useless. If it offers incorrect information, it’s unnecessary. Algorithms get training to learn how to process information. The efficiency, the accuracy, and the speed depend on the training quality.
When you use an algorithm to come up with the right answer, it doesn’t automatically mean using AI and/or ML. But if you are using AI and ML, you are taking advantage of the algorithms.
All humans have eyes, but not all creatures who have eyes are human.
These days, we hear about AI and ML being used whenever an algorithm exists. Using an algorithm to predict event outcomes doesn’t involve machine learning. Using the outcome to improve the future predictions does.
What Is Artificial Intelligence?
AI is a widely used term. It’s a science of making the computer

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