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

Artificial Intelligence is a broad field that encompasses various subfields, such as rule-based systems, decision trees, expert systems, and machine learning. AI involves the development of computer systems that can perform tasks that would normally require human intelligence, such as visual perception, speech recognition, decision-making, and language understanding.

Machine Learning, on the other hand, is a subfield of AI that involves the development of algorithms and statistical models that enable computers to learn from data, without being explicitly programmed. It allows computers to improve their performance on a specific task by learning from experience, without the need for explicit instructions. Machine Learning algorithms can be used to solve a wide variety of problems, such as image recognition, natural language processing, and predictive modeling.

In simpler terms, AI is the broader concept of making machines smart and able to do things that would normally require human intelligence. Machine learning is a way of achieving AI, where computers are able to learn from data instead of being explicitly programmed.