How can AI, machine learning, and deep learning be correctly differentiated?

The correct choice highlights that AI is an overarching field that encompasses various techniques, including machine learning and deep learning. In this framework, AI represents any technique that enables machines to mimic human-like intelligence, which can include everything from rule-based systems to advanced algorithms.

Machine learning, as a subset of AI, refers to systems that learn from data to improve their performance over time without explicit programming. Deep learning, in turn, is a specialized branch of machine learning that employs neural networks with multiple layers to process data with great complexity and sophistication. This layered approach allows deep learning models to extract features and make decisions based on vast amounts of unstructured data, like images and text.

The distinction is crucial for understanding the hierarchy of these technologies. While all deep learning is machine learning, not all machine learning is deep learning, and both are part of the larger domain of artificial intelligence. This organization helps clarify the capabilities and applications of each area within the broader context of AI.