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Exam AWS Certified AI Practitioner AIF-C01 All Questions

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Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 192 discussion

What is the purpose of vector embeddings in a large language model (LLM)?

  • A. Splitting text into manageable pieces of data
  • B. Grouping a set of characters to be treated as a single unit
  • C. Providing the ability to mathematically compare texts
  • D. Providing the count of every word in the input
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Suggested Answer: C 🗳️

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a6558c7
3 weeks, 5 days ago
Selected Answer: C
C. Providing the ability to mathematically compare texts The other options are incorrect because: A. Splitting text into manageable pieces is related to chunking or tokenization, not embeddings. B. Grouping characters as a single unit relates to tokenization or subword units. D. Counting every word is related to bag-of-words models or frequency counts, not embeddings.
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