AI0-001 AI Concepts and Techniques Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Machine learning

  Why it's wrong here

  Machine learning is a method for deriving models from data, not a category describing breadth of intellectual capability. It is tempting because it is the dominant AI paradigm, and would be correct when the question asks how a system improves performance through experience rather than how general its abilities are.

• ✓

  Artificial General Intelligence (AGI)

  Why this is correct

  Artificial General Intelligence denotes a system matching human capability across any intellectual task, including reasoning, learning and transfer between domains. This contrasts with narrow AI, which is confined to a single specific task such as image classification.

• ✗

  Narrow AI

  Why it's wrong here

  Narrow AI performs a single task or limited domain, so it cannot match general human intellectual capability. It is tempting because most deployed systems today are narrow, and the term would be correct when describing a system restricted to one function, such as image classification or recommendation.

• ✗

  Deep learning

  Why it's wrong here

  Deep learning is a neural-network training technique, not a capability classification, so it says nothing about performing any human intellectual task. It is tempting because deep learning underpins many advanced systems, and would be correct when the question asks about the method used to train a model on large datasets.