Generative AI Interview Questions, Answers for Freshers and Experienced asked in various Company Job Interviews

Generative AI Interview Questions

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Which developer tools and frameworks are most commonly used with LLMs?

Why is data governance critical in managing LLMs?

How can governance be extended to all data types?

What steps are involved in defining the use case and scope of an LLM project?

How can one select the right LLM for a specific project?

What factors should be considered when comparing small and large language models?

What strategies can be used to adapt LLMs to a specific use case?

What are prompt engineering techniques, and how can they improve LLM outputs?

How does learning from context enhance the performance of LLMs?

What is text retrieval augmentation, and why is it important?

What are the key steps involved in fine-tuning language models?

Can you explain reinforcement learning and its role in improving LLMs?

What is a vector database, and how is it used in LLM applications?

How can data pipelines be adapted for LLM applications?

How can organizations identify business problems suitable for Generative AI?

Un-Answered Questions { Generative AI }

What is a Large Language Model (LLM), and how does it work?

How can latency be reduced in LLM-based applications?

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How does multimodal AI enhance Generative AI applications?

How do you ensure that your LLM generates contextually accurate and meaningful outputs?

What is the role of containerization and orchestration in deploying LLMs?

How do AI agents function in orchestration, and why are they significant for LLM apps?

Describe the Transformer architecture used in modern LLMs.

How do you balance transparency and performance in Generative AI systems?

Can you explain the difference between discriminative and generative models?

What is hallucination in LLMs, and how can it be controlled?

How does a cloud data platform help in managing Gen AI projects?

How can the costs of LLM inference and deployment be calculated and optimized?

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What is context retrieval, and why is it important in LLM applications?

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How will quantum computing impact Generative AI?

What are the trade-offs between security and ease of use in Gen AI applications?

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