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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 21 discussion

Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?

  • A. Integration with Amazon S3 for object storage
  • B. Support for geospatial indexing and queries
  • C. Scalable index management and nearest neighbor search capability
  • D. Ability to perform real-time analysis on streaming data
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Suggested Answer: C 🗳️

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Jessiii
2 weeks, 6 days ago
Selected Answer: C
Scalable index management and nearest neighbor search capability: Amazon OpenSearch Service provides built-in support for vector search, which allows for efficient nearest neighbor search (such as k-nearest neighbors or k-NN) in large datasets. This is essential for vector databases, which store high-dimensional data (such as embeddings from machine learning models) and support fast similarity search. The scalable index management ensures that these searches can be performed efficiently even with large datasets.
upvoted 2 times
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85b5b55
1 month ago
Selected Answer: C
Scalable index management and k-NN algorithms which support to build and handle the recommendation systems, semantic search and anomalies detection.
upvoted 1 times
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Moon
2 months ago
Selected Answer: C
C: Scalable index management and nearest neighbor search capability Explanation: The Amazon OpenSearch Service supports building vector database applications by enabling nearest neighbor search capability. This feature allows the service to efficiently perform similarity searches, which is crucial for applications that rely on vector embeddings (e.g., recommendation systems, image or text similarity searches). Combined with scalable index management, this makes OpenSearch an excellent choice for vector database applications.
upvoted 1 times
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ap6491
2 months ago
Selected Answer: C
Amazon OpenSearch Service provides scalable index management and supports nearest neighbor (k-NN) search, which is essential for building vector database applications. Vector databases store embeddings (numerical representations of data) and use k-NN search to retrieve similar data points based on proximity in the vector space, which is a foundational feature for applications such as recommendation systems, semantic search, and anomaly detection. These capabilities make OpenSearch ideal for developing vector-based applications.
upvoted 1 times
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Blair77
3 months, 3 weeks ago
c- The key feature of Amazon OpenSearch Service that enables companies to build vector database applications is its k-NN (k-nearest neighbors) functionality, specifically provided through the k-NN plugin. This allows OpenSearch Service to act as a vector database with efficient vector similarity search capabilities.
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jove
3 months, 4 weeks ago
Selected Answer: C
Amazon OpenSearch Service provides scalable index management and nearest neighbor search capabilities, which are essential for building vector database applications.
upvoted 2 times
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