If you are a person who uses the internet, no matter how old you are, you might have heard the term AI in recent years. Some of us are also familiar with the terms Machine Learning and Deep Learning. Now, let’s say we have some idea about what AI is from Tesla’s self-driving cars, MidJourney AI, or our very popular ChatGPT. But then, what is Machine Learning or Deep Learning? Are they the same? Are they different? What are the differences? Which is which? These kinds of questions commonly pop up in our minds. So, in this article, we are going to clear up our confusion about these terms.
Deep Learning:
Let’s start with a bit of biology. Our brain contains neurons, which make connections with each other and transmit information through electrical signals. Our brain learns new things by forming new connections between neurons. Deep learning is a similar concept. It is based on neural networks. Through this neural network, it learns from past experiences and repetitions. It requires a large set of data to learn from. Its accuracy is very high and doesn’t require any human intervention. It can solve non-linear and complex problems. For example, if we want to make a black-and-white photo colorful, it will learn from a large dataset of pictures what the colors in a black-and-white image might be.
Machine Learning:
Machine learning is a combination of deep learning and statistical models. It is a broader concept than deep learning. It also makes decisions by itself but requires human intervention when the results are not good and when adjustments to decision-making algorithms are needed. It does not provide results as accurate as deep learning. Machine learning trains a model on smaller data sets and creates simpler, linear relationships. For example, if you are an engineer at YouTube and have been given the task to build a machine learning algorithm that predicts what a viewer likes and what types of videos they watch, and suggests new content based on that, doing this purely with code would be nearly impossible. But by implementing statistical models, YouTube gets an idea of what videos a viewer may like. It learns by itself what to suggest.
Artificial Intelligence:
AI is the broad concept of creating human-like intelligence based on computer science, statistics, machine learning, and other fields. A robot that can perform some physical tasks by itself is also considered AI. To build such a robot, we also need other systems to collect data. So, AI is the combination of everything required to make a machine think or act like a human.
