多模态 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

30 道原题
  1. What are Multimodal AI models, and how do they process different types of data?

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  2. How do vision-language models process images?

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  3. How do Image Embeddings work?

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  4. How does CLIP work, and why is it important for multi-modal AI?

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  5. What are the key architectures for multi-modal models?

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  6. How does image generation work with diffusion models (Stable Diffusion, DALL-E, Flux)?

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  7. What is text-to-speech (TTS), and what models are used for it?

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  8. How does speech-to-text (Whisper) work?

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  9. Budget the end-to-end latency for a real-time voice agent (VAD, ASR, LLM, TTS, network). Where does the time go?

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  10. How do you handle barge-in (user interruptions) in a voice agent?

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  11. Cascaded ASR + LLM + TTS vs native speech-to-speech models: what are the trade-offs?

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  12. What is multi-modal RAG, and how does it differ from text-only RAG?

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  13. How do you build a system that processes both images and text?

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  14. What are multi-modal embeddings, and how are they used for cross-modal search?

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  15. How do you evaluate multi-modal AI systems?

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  16. What are the challenges of real-time multi-modal AI processing?

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  17. How do you handle video understanding with AI?

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  18. What is visual question answering (VQA)?

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  19. What is document understanding, and how do models parse documents with layouts?

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  20. How do you fine-tune a vision-language model?

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  21. What are the latency and cost considerations for multi-modal AI in production?

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  22. How do you handle multi-modal content moderation?

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  23. What is text-to-video generation, and what are the current state-of-the-art approaches?

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  24. Explain Multimodal Fusion Techniques: Early Fusion vs Late Fusion.

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  25. Your vision-language model generates factually incorrect image descriptions. How do you fix it?

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  26. Your VLM answers single-image questions but fails on multi-page documents. How do you fix it?

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  27. Your multimodal LLM ignores the image and generates descriptions from text alone. How do you fix it?

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  28. Your diffusion model ignores precise control requirements in text prompts. How do you improve controllability?

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  29. Your diffusion model generates sharp but repetitive images. How do you balance quality vs diversity?

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  30. Your diffusion model takes too long per image. How do you speed up sampling?

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