Which of the following best describes the relationship between Machine Learning and Artificial Intelligence?

The relationship between Machine Learning and Artificial Intelligence is accurately described by stating that Machine Learning is a method to achieve AI, but they are not the same. Artificial Intelligence encompasses a broad range of techniques and systems designed to simulate human intelligence to perform tasks such as problem-solving, reasoning, and understanding language. Within this vast field, Machine Learning serves as a specific approach that enables systems to learn from data, thereby improving their performance over time without being explicitly programmed for each task.

This distinction is crucial because while all Machine Learning is considered a part of Artificial Intelligence, not all AI relies on Machine Learning methods. AI can involve other techniques and domains, such as rule-based systems, expert systems, and more traditional programming approaches. Recognizing that Machine Learning is one of many methodologies used to create intelligent systems helps clarify the broader context of Artificial Intelligence as a discipline.

The other options inaccurately confuse these two important concepts: suggesting they are identical misrepresents their relationship, whereas the idea that AI is a subset of Machine Learning reverses the correct hierarchy. Additionally, portraying Machine Learning as less complex oversimplifies a field that encompasses a range of methodologies used to tackle complex problems within AI.