A new analyst is learning how the terms artificial intelligence, machine learning, and deep learning relate to one another as nested fields. Which two statements correctly describe this relationship? Select TWO.
- AArtificial intelligence is one specialised technique that sits entirely inside the broader field of machine learning.
- BMachine learning is a subset of artificial intelligence in which systems learn patterns from data rather than following hand-coded rules. Correct
- CDeep learning and machine learning are two separate disciplines that share no methods and never overlap in practice.
- DDeep learning is a subset of machine learning that uses neural networks with many stacked layers to learn features. Correct
- EArtificial intelligence, machine learning, and deep learning are interchangeable synonyms for exactly the same single concept.
Why A is wrong: This reverses the actual nesting; machine learning is a subset of artificial intelligence, not the other way around, so the containment is backwards.
Why B is correct: Machine learning is correctly framed as a branch of the wider artificial intelligence field, defined by learning from data instead of explicit rules.
Why C is wrong: This is tempting because the names differ, but deep learning is a subset of machine learning, so the two clearly overlap rather than being separate.
Why D is correct: Deep learning is accurately placed inside machine learning and characterised by multi-layer neural networks that learn representations directly.
Why E is wrong: Treating the three as identical ignores their nesting; each names a progressively narrower field, so they are related but not interchangeable.