AI Vs Machine Learning

 Artificial Intelligence (AI) and Machine Learning (ML) are closely related, but distinct concepts in the field of computer science.

AI is a broad term that refers to the development of intelligent machines that can perform tasks that typically require human intelligence, such as perception, reasoning, learning, and decision-making. AI encompasses a wide range of technologies, including machine learning, natural language processing, computer vision, robotics, and expert systems.

Machine learning, on the other hand, is a specific subset of AI that focuses on training computer algorithms to learn from data and make predictions or decisions based on that data, without being explicitly programmed. Machine learning is a form of artificial intelligence that enables machines to learn and improve from experience.

In other words, AI is the broader concept of creating intelligent machines that can mimic human intelligence, while machine learning is a specific technique within AI that involves training algorithms to learn from data.

To give an example, self-driving cars are an application of AI, as they are designed to perform a task that typically requires human intelligence (driving a car). Machine learning is used in self-driving cars to train the algorithm to recognize different objects on the road, such as other cars, pedestrians, and traffic signals, and make decisions based on that information.

In summary, AI is the general concept of creating intelligent machines, while machine learning is a specific technique within AI that involves training algorithms to learn from data.