What is the difference between AI and machine learning?

AI (Artificial Intelligence) and Machine Learning (ML) are related but distinct concepts.

AI refers to the development of computer systems that can perform tasks that typically require human intelligence, such as perception, reasoning, learning, and decision-making. AI can be applied to a wide range of fields, including natural language processing, computer vision, robotics, and more.

Machine Learning, on the other hand, is a subset of AI that involves training computer algorithms to learn from data, without being explicitly programmed. In other words, it is the process of feeding large amounts of data to a machine learning algorithm, so that it can recognize patterns and make predictions based on new data. The machine learning algorithms can be divided into three categories - supervised, unsupervised, and reinforcement learning.

In simpler terms, AI is the larger field that encompasses any system that can perform tasks that normally require human intelligence. Machine learning is a specific approach within the AI field that involves the use of algorithms to enable a machine to learn and make decisions based on data, without being explicitly programmed. Therefore, machine learning is a subset of AI that focuses on a particular approach to solving problems.