Why is machine learning considered integral to artificial intelligence?

Machine learning is considered integral to artificial intelligence because it enables systems to learn and improve from experience, which is a fundamental aspect of how intelligent behavior is realized in machines. By utilizing algorithms that can analyze and learn patterns from data, machine learning allows AI systems to develop capabilities that evolve over time without needing explicit programming for every specific task.

This characteristic of learning from experience contrasts with traditional programming methods, where a programmer would manually dictate the rules and logic needed to perform a task. Machine learning systems can adapt to new inputs and scenarios, enhancing their performance and accuracy over time, which closely resembles cognitive learning in humans.

The other options do not accurately capture the essence of machine learning's role in AI. Some suggest methods that are contrary to the learning aspect, while others propose functions that are not aligned with the core functionality of machine learning in creating adaptable and intelligent systems.