安全与可信 AI

题集来源:AMIT SHEKHAR(amitshekhariitbhu)收录项目:ai-engineering-interview-questions查看原题集

题目目录

45 道原题
  1. What are hallucinations in LLMs, and how do you mitigate them?

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  2. What is prompt injection, and what are the different types (direct, indirect)?

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  3. How do you implement input and output guardrails for AI systems?

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  4. What is AI alignment, and why is it important?

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  5. How do you detect and mitigate bias in AI systems?

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  6. What are the key data privacy considerations (GDPR, CCPA) when building AI applications?

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  7. How do you handle PII in LLM inputs and outputs?

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  8. What is explainability in AI, and why does it matter?

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  9. What is the difference between interpretability and explainability?

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  10. What is mechanistic interpretability, and why do AI labs invest in it?

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