In this growing digital era, AI, ML, and DL are often considered synonymous terms. But they are not the same, but have similar meaning and within the close spectrum of one another, each represents a distinct technological layer. These concepts range from chatbots answering your questions to giving Uber drivers their directions to self-driving cars making decisions to stay safe on a busy road. Referring to changes in the lifestyles of working and interacting with machines, we need to consider the differences between AI, ML, and DL and how, in tandem, they provide momentum to the front edge of modern technology.

What is Artificial Intelligence (AI)?

Artificial Intelligence is where you can build machines/software with your intellectual capabilities, and you can make them similar to human beings. It entails reasoning, judgment, and decision-making. Systems can be rule-based, such as chatbots, or advanced, such as self-driving cars.

What is Machine Learning (ML)?

Machine Learning is a method by which computers develop pattern recognition, or the ability to learn, without being explicitly programmed. An ML model studies data, recognizes patterns, and derives an inference. Examples include recommendation systems, email spam filters, and fraud detection.

What is Deep Learning, DL? 

Deep Learning is a special branch of ML that uses multilayered artificial neural networks. Usually, deep learning is inspired by the human mind and processes large amounts of data to find intricate patterns. Applications that use this technology in the most helpful ways include voice recognition, medical imaging, facial recognition, and driverless cars.

Simple Comparison

AI = The big goal → making machines intelligent.
ML = A way to achieve AI → learning from data.
DL = An advanced technique in ML → using deep neural networks.