Deep Learning & Generative AI

Generative AI & Large Language Models (LLMs) Interview Questions

Interview questions on Generative AI & Large Language Models (LLMs) Interview Questions.

22 questions

All subtopics LLM Architectures & Foundations Tokenization & Embeddings Attention, KV Cache & Efficient Inference LLM Training & Pre-training Decoding Strategies & Prompt Engineering Fine-Tuning & Model Adaptation RAG & Vector Databases Alignment & Preference Optimization LLM Evaluation & Benchmarking Agents, Tool Use & Memory Multimodal Generative AI LLM Safety & Security LLMOps & Production

LLM Architectures & Foundations

Q1. What is a Language Model?

LLM Architectures & Foundations

Q2. What are autoregressive language models?

LLM Architectures & Foundations

Q3. How do autoregressive models employ the chain rule of probability?

LLM Architectures & Foundations

Q4. What are different types of language models?

LLM Architectures & Foundations

Q5. What are encoder-only language models?

LLM Architectures & Foundations

Q6. State the pros and cons of an encoder-only language model?

LLM Architectures & Foundations

Q7. What are decoder-only language models?

LLM Architectures & Foundations

Q8. What are pros and cons of decoder-only language models?

LLM Architectures & Foundations

Q9. What are encoder-decoder language models?

LLM Architectures & Foundations

Q10. What are pros and cons of encoder-decoder language models?

LLM Architectures & Foundations

Q11. What is the difference between proprietary and open-source Large Language Models (LLMs)?

LLM Architectures & Foundations

Q12. What is the context window in LLMs, and why does it matter?

LLM Architectures & Foundations

Q13. How can we use an encoder-only model for classification tasks?

LLM Architectures & Foundations

Q14. What are sequence-to-sequence models, and where are they applied?

LLM Architectures & Foundations

Q15. What is the difference between representation models and generative models?

LLM Architectures & Foundations

Q16. What are emergent properties of LLMs?

LLM Architectures & Foundations

Q17. What are generative versus discriminative models in NLP?

LLM Architectures & Foundations

Q18. How does GPT-4 differ from GPT-3 in features and applications?

LLM Architectures & Foundations

Q19. What types of foundation models exist?

LLM Architectures & Foundations

Q20. How do discriminative and generative AI differ?

LLM Architectures & Foundations

Q21. How do LLMs differ from traditional statistical language models?

LLM Architectures & Foundations

Generative AI & Large Language Models (LLMs) Interview Questions

Q1. What is a Language Model?

Q2. What are autoregressive language models?

Q3. How do autoregressive models employ the chain rule of probability?

Q4. What are different types of language models?

Q5. What are encoder-only language models?

Q6. State the pros and cons of an encoder-only language model?

Q7. What are decoder-only language models?

Q8. What are pros and cons of decoder-only language models?

Q9. What are encoder-decoder language models?

Q10. What are pros and cons of encoder-decoder language models?

Q11. What is the difference between proprietary and open-source Large Language Models (LLMs)?

Q12. What is the context window in LLMs, and why does it matter?

Q13. How can we use an encoder-only model for classification tasks?

Q14. What are sequence-to-sequence models, and where are they applied?

Q15. What is the difference between representation models and generative models?

Q16. What are emergent properties of LLMs?

Q17. What are generative versus discriminative models in NLP?

Q18. How does GPT-4 differ from GPT-3 in features and applications?

Q19. What types of foundation models exist?

Q20. How do discriminative and generative AI differ?

Q21. How do LLMs differ from traditional statistical language models?

Q22. What defines a Large Language Model (LLM)?