IVQ 1-50
Section 1: Fundamentals (10 Questions)
What is Generative AI and how does it differ from traditional AI?
Can you explain how a Transformer architecture works?
What are the key differences between GPT, BERT, and T5?
How do attention mechanisms work in large language models?
What is the difference between autoregressive and autoencoding models?
Explain the concept of tokenization in NLP.
What is the role of positional encoding in Transformers?
Define "prompt engineering" and give an example.
What is fine-tuning vs. instruction-tuning?
What are hallucinations in GenAI models?
Section 2: Practical Application (10 Questions)
How would you generate synthetic data using a GenAI model?
How do you prevent sensitive data from leaking in GenAI outputs?
What’s your experience with OpenAI APIs or Hugging Face Transformers?
Describe a real-world use case where you applied GenAI.
How do you evaluate the output of a GenAI model?
What is prompt chaining and when would you use it?
How would you use GenAI for summarization or translation?
Can you integrate a GenAI model into a chatbot? How?
How do you cache responses for cost-effective GenAI use?
How would you deploy a GenAI model in production?
Section 3: Advanced Techniques (10 Questions)
What is Retrieval-Augmented Generation (RAG)?
How do you implement Guardrails in a GenAI pipeline?
Compare LoRA, QLoRA, and PEFT.
What’s the difference between GPTQ and AWQ quantization?
How does multi-modal generation work? Any examples?
How can you use GenAI for code generation tasks?
How do you fine-tune a large model using limited compute?
Explain Reinforcement Learning with Human Feedback (RLHF).
What is Self-Consistency Sampling and when is it used?
How do you detect and reduce bias in GenAI models?
Section 4: GenAI + Ecosystem Tools (10 Questions)
What’s the role of LangChain in GenAI orchestration?
Compare LangChain and Haystack.
How does LangGraph differ from AutoGen?
What is an embedding model and how is it used with GenAI?
How do you use vector databases like Qdrant, Weaviate, or FAISS in GenAI?
What are agents in GenAI workflows?
What is the role of Pinecone or Milvus in GenAI apps?
How would you use Prefect or Airflow with a GenAI pipeline?
How do you design a GenAI-powered document QA system?
How can you leverage OpenAI functions or tools like Toolformer?
Section 5: Trends & Ethics (10 Questions)
What are the major risks of using GenAI in enterprise applications?
How do you handle misinformation and hallucination in outputs?
What are the key concerns around copyright and GenAI?
How do you stay updated with GenAI trends and models?
What’s your opinion on open-source vs. closed-source LLMs?
What regulatory or ethical frameworks impact GenAI usage?
How do you anonymize training data in GenAI applications?
What are the best practices for model governance in GenAI?
How do you evaluate factual accuracy in LLM-generated content?
What’s your perspective on the future of agentic AI systems?
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