{"id":2868,"date":"2026-08-09T14:55:04","date_gmt":"2026-08-09T14:55:04","guid":{"rendered":"https:\/\/blog.passtestking.com\/?p=2868"},"modified":"2026-08-09T14:55:04","modified_gmt":"2026-08-09T14:55:04","slug":"nca-genm-exam-questions-get-updated-2026-with-correct-answers-q22-q36","status":"publish","type":"post","link":"https:\/\/blog.passtestking.com\/ko\/2026\/08\/09\/nca-genm-exam-questions-get-updated-2026-with-correct-answers-q22-q36\/","title":{"rendered":"NCA-GENM Exam Questions Get Updated [2026] with Correct Answers [Q22-Q36]"},"content":{"rendered":"\n\n
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NCA-GENM Exam Questions Get Updated [2026] with Correct Answers<\/span><\/strong><\/p>\n

Practice NCA-GENM Questions With Certification guide Q&A from Training Expert PassTestking<\/span><\/strong><\/p>\n

NVIDIA NCA-GENM Exam Syllabus Topics:<\/h3>\n\n\n\n\n\n\n\n\n
Section<\/th>\nObjectives<\/th>\n<\/tr>\n
Topic 1: Multimodal AI Systems<\/td>\n– Multimodal model design
\n– Cross-modal learning<\/p>\n
    \n
  • 1. Text-image integration\n
      <\/ul>\n<\/li>\n
    • 2. Audio-visual understanding\n
        <\/ul>\n<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
Topic 2: Core AI and Machine Learning Fundamentals<\/td>\n– Machine learning basics<\/p>\n
    \n
  • 1. Supervised and unsupervised learning\n
      <\/ul>\n<\/li>\n
    • 2. Neural networks fundamentals\n
        <\/ul>\n<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
Topic 3: Responsible and Trustworthy AI<\/td>\n– Ethical AI principles
\n– Bias and safety considerations\n<\/td>\n<\/tr>\n
Topic 4: NVIDIA AI Ecosystem<\/td>\n– NVIDIA tools and frameworks<\/p>\n
    \n
  • 1. NeMo framework usage\n
      <\/ul>\n<\/li>\n
    • 2. GPU-accelerated AI workflows\n
        <\/ul>\n<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
Topic 5: Generative AI Concepts<\/td>\n– Generative models<\/p>\n
    \n
  • 1. Diffusion models\n
      <\/ul>\n<\/li>\n
    • 2. Transformers and LLM basics\n
        <\/ul>\n<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

         <\/p>\n

        \n
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        QUESTION 22<\/strong>
        Consider a system that generates captions for images, and a key metric is BLEU score. You observe that while the BLEU score is high, the generated captions often lack detailed descriptions of the objects and relationships within the image. Which of the following strategies would you employ to improve the descriptive richness of the generated captions?<\/p>\n<\/div>