Artificial intelligence (AI) and machine learning (ML) are related but distinct fields in computer science.

AI is a broad term that refers to the ability of a machine or computer program to perform tasks that typically require human-like intelligence, such as understanding natural language, recognizing images, making decisions, and learning from experience. AI can be achieved through a variety of techniques, including rule-based systems, decision trees, and neural networks.

On the other hand, ML is a subfield of AI that focuses on algorithms and statistical models that enable machines to improve their performance on a specific task based on data inputs. In other words, ML is a method for achieving AI. ML algorithms are designed to analyze data, identify patterns, and make predictions or decisions without being explicitly programmed.

In short, AI is the broader field that encompasses all aspects of machine intelligence, while ML is a specific subset of AI that focuses on developing algorithms that can learn and improve based on data inputs.
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