A wildlife conservation agency operates zoos globally. The agency uses various sensors, trackers, and audiovisual recorders to monitor animal behavior. The agency wants to launch a generative AI…

Question

Options

• AIngest raw videos into Amazon Rekognition to detect animal postures and expressions. Use
• BUse Amazon SageMaker Processing and Amazon Transcribe to pre-process multimodal data.
• CUse Amazon OpenSearch Serverless to index behavioral logs and telemetry. Use Amazon
• DConfigure Amazon O Business to federate data across Amazon S3, Amazon Kinesis, and

• A
  3% (1)
• B
  77% (23)
• C
  7% (2)
• D
  13% (4)

Explanation

Option B best meets the multimodal, ethical, and auditability requirements using managed AWS services designed for research-grade GenAI systems. Multimodal data such as audio, video, sensor telemetry, and tracking data must be curated and summarized before being consumed by a foundation model. Amazon SageMaker Processing and Amazon Transcribe provide scalable, managed preprocessing for audiovisual and textual data. By ingesting summarized, validated observations into Amazon Bedrock Knowledge Bases, the GenAI assistant can answer natural language queries using grounded, evidence-based context instead of raw sensor signals. This significantly reduces the risk of speculative or anthropomorphic interpretations. Amazon Bedrock guardrails are critical for preventing speculative behavioral claims, enforcing scientific and ethical constraints at inference time. Guardrails provide a validated, auditable safety layer that custom Lambda-based filters cannot reliably replicate. AWS AppConfig enables controlled prompt management and change governance, ensuring that research prompts remain consistent and reviewable. AWS CloudTrail captures all access, query, and configuration changes, supporting ethical research audits and regulatory reviews.

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