How do you balance innovation with practical business constraints?

35

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How do you select the right model architecture for a specific Generative AI application?

28

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What are the key differences between GPT, BERT, and other LLMs?

42

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How would you adapt a pre-trained model to a domain-specific task?

29

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What are some techniques to improve LLM performance for specific use cases?

32

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

36

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What is prompt engineering, and why is it important for Generative AI models?

42

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How do you design prompts for generating specific outputs?

35

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What are some best practices for crafting effective prompts?

30

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How do few-shot and zero-shot learning influence prompt engineering?

29

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Can you explain the difference between discriminative and generative models?

34

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Can you provide examples of how to structure prompts for a given use case?

45

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Why is data quality critical in Generative AI projects?

28

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How do you prepare and clean data for training a generative model?

33

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What techniques are used for handling noisy or incomplete data?

32

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