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Generative AI Objective Questions and Answers - Set 3
This Generative AI quiz contains carefully curated objective questions with correct answers and clear explanations. It is designed for developers, AI engineers, and interview preparation, covering modern generative models, architectures, optimization techniques, and practical applications. This is part 3 of the series.
Practice Generative AI MCQs with Detailed Explanations
Answer at least 12 questions to submit and verify answers.
31 Which reduces bias? Medium
Correct answer:
Better datasets
Quality datasets reduce bias.
32 What is perplexity? High
Correct answer:
Measure of prediction uncertainty
Lower perplexity indicates better predictions.
33 Which improves latency? Medium
Correct answer:
Model optimization
Optimizations reduce response time.
34 What is beam search? High
Correct answer:
Search algorithm for sequence generation
Beam search explores multiple sequences.
35 What is greedy decoding? Medium
Correct answer:
Selecting highest probability token
Greedy decoding picks most probable token.
36 Which improves quality vs speed tradeoff? High
Correct answer:
Beam search
Beam search improves quality at cost of speed.
37 What is fine-tuning vs prompting? Medium
Correct answer:
Training vs input design
Fine-tuning changes model weights, prompting changes input.
38 Which is cost-efficient? Medium
Correct answer:
Prompt engineering
Prompting avoids retraining costs.
39 What is knowledge cutoff? Medium
Correct answer:
Training data time limit
Models are trained on data up to a certain time.
40 Which is evaluation metric? Medium
Correct answer:
All of the above
Multiple metrics evaluate generative models.
41 What is model quantization? High
Correct answer:
Reducing model size using lower precision
Quantization reduces size and improves speed.
42 Which improves memory efficiency? High
Correct answer:
Quantization
Quantization reduces memory usage.
43 What is LoRA? High
Correct answer:
Low-Rank Adaptation
LoRA is efficient fine-tuning technique.
44 Which is parameter-efficient tuning? High
Correct answer:
LoRA
LoRA reduces training cost.
45 Which improves overall Generative AI systems? Medium
Correct answer:
Better models, prompts, and data
Holistic optimization yields best results.