Why is data quality critical in Generative AI projects?

44

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

45

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What techniques are used for handling noisy or incomplete data?

42

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Explain the importance of tokenization in LLMs.

72

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What is the role of vector embeddings in Generative AI?

38

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What are the benefits and challenges of fine-tuning a pre-trained model?

51

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How do you decide whether to fine-tune or train a model from scratch?

47

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What is reinforcement learning with human feedback (RLHF), and how is it applied?

51

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How do you prevent overfitting during fine-tuning?

79

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What are some real-world applications of Generative AI?

58

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What metrics do you use to evaluate the performance of a fine-tuned model?

41

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What are the best practices for deploying Generative AI models in production?

53

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How do you optimize LLMs for low-latency applications?

43

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What challenges arise when scaling LLMs for large-scale usage?

71

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How do you integrate Generative AI models with existing enterprise systems?

45

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