Artificial intelligence and machine learning are part of the computer science field. Both terms are correlated and most people often use them interchangeably. However, AI and machine learning are not the same and there are some key differences that I will discuss here. So, without further ado, let’s go into the details to know the difference between AI and machine learning.
Artificial intelligence is a machine’s ability to solve tasks that are commonly done by intelligent beings or humans. So, AI allows machines to execute tasks “smartly” by imitating human abilities. On the other hand, machine learning is a subset of Artificial intelligence. It is the process of learning from data that is fed into the machine in the form of algorithms.
Artificial Intelligence and its Real-World Benefits
Artificial intelligence is the science of training computers and machines to perform tasks with human-like intelligence and reasoning skills. With AI in your computer system, you can speak in any accent or any language as long as there is data on the internet about it. AI will be able to pick it up and follow your commands.
We can see the application of this technology in a lot of the online platforms that we enjoy today, such as retail stores, healthcare, finance, fraud detection, weather updates, traffic information and much more. As a matter of fact, there is nothing that AI cannot do.
Machine Learning and its Process
This is based on the idea that machines should be able to learn and adapt through experience. Machine learning can be done by giving the computer examples in the form of algorithms. This is how it will learn what to do on the basis of the given examples.
Once the algorithm determines how to draw the right conclusions for any input, it will then apply the knowledge to new data. And that is the life cycle of machine learning. The first step is to collect data for a question you have. Then the next step is to train the algorithm by feeding it to the machine.
You will have to let the machine try it out, then collect feedback and use the information you gained to make the algorithm better and repeat the cycle until you get your desired results. This is how the feedback works for these systems.
Machine learning uses statistics and physics to find specific information within the data, without any specific programming about where to look or what conclusions to draw. These days’ machine learning and artificial intelligence are applied to all sorts of technology. Some of them include CT scan, MRI machines, car navigation systems and food apps, to name a few.
In simple words, artificial intelligence is the science of creating machines that have human-like properties of reasoning and problem-solving. And this allows machines to learn and make decisions from past data without explicit programming. In short, the goal of AI is to create intelligent machines. And it does that by combining machine learning and deep learning etc.