How do AI, machine learning, and deep learning differ from one another?

The correct answer highlights the hierarchical relationship between AI, machine learning, and deep learning, illustrating how they are interconnected yet distinct entities within the field of artificial intelligence.

Artificial Intelligence (AI) is indeed the broadest concept, encompassing any technique that enables computers to mimic human behavior, including perception, reasoning, learning, and problem-solving. Within this expansive field lies machine learning, which is a subset of AI focused specifically on the development of algorithms that allow computers to learn from and make predictions based on data. This learning is characterized by the system's ability to improve its performance over time without being explicitly programmed to do so.

Deep learning, on the other hand, is a further subset of machine learning. It employs neural networks with many layers to analyze various factors of data and extract high-level abstractions. This has proven particularly effective in complex tasks such as image and speech recognition. Thus, deep learning can be seen as an advanced methodology within machine learning that significantly enhances its capabilities.

The other options do not accurately reflect the relationships and distinctions among these concepts. Understanding this hierarchy is crucial for grasping how AI, machine learning, and deep learning contribute to advancements in technology and practical applications in various fields.