Why is learning a distribution more powerful than memorizing examples?
Answer options
A
It guarantees exact copies
B
It allows sampling novel but plausible items
C
It reduces compute to zero
D
It avoids any bias automatically
Correct answer: It allows sampling novel but plausible items
Explanation
Quick AnswerThe correct answer is It allows sampling novel but plausible items because it directly addresses the core logic of Generative AI.
Learning a data distribution allows a model to generate novel but plausible samples, unlike mere memorization which can only reproduce training examples.