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Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 110 discussion

Exam question from Amazon's AWS Certified AI Practitioner AIF-C01
Question #: 110
Topic #: 1
[All AWS Certified AI Practitioner AIF-C01 Questions]

A company is implementing intelligent agents to provide conversational search experiences for its customers. The company needs a database service that will support storage and queries of embeddings from a generative AI model as vectors in the database.

Which AWS service will meet these requirements?

  • A. Amazon Athena
  • B. Amazon Aurora PostgreSQL
  • C. Amazon Redshift
  • D. Amazon EMR
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Suggested Answer: B 🗳️
by 26b8fe1 at Dec. 26, 2024, 3:25 p.m.
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Jessiii
4 months, 1 week ago
Selected Answer: B
Supports pgvector, a popular extension for storing and querying vector embeddings.
upvoted 1 times
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may2021_r
5 months, 3 weeks ago
Selected Answer: B
The correct answer is B. Amazon Aurora PostgreSQL supports vector data types and can efficiently store and query embeddings.
upvoted 1 times
...
aws_Tamilan
5 months, 3 weeks ago
Selected Answer: B
Amazon Aurora PostgreSQL is the best choice for a database service to store and query embeddings from generative AI models, as it supports vector storage and similarity searches through the pgvector extension.
upvoted 1 times
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26b8fe1
5 months, 4 weeks ago
Selected Answer: B
Amazon Aurora PostgreSQL Amazon Aurora PostgreSQL supports vector storage and queries, making it suitable for storing embeddings from a generative AI model as vectors in the database. It integrates with extensions like pgvector to efficiently handle high-dimensional vector data.
upvoted 1 times
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