AWS Certification Exam AI Practitioner (Practice Questions) set6

問題 65 / 65

When improving a global AI model, which approach is most appropriate for keeping each country's data local and minimizing cross-border data transfers?

Aggregate raw data from various locations to a central location for training.
Generate synthetic data and train centrally.
Transfer with only differential privacy applied.
Encrypt everything with homomorphic encryption and perform centralized training.
Federated learning (training at each site with only model updates shared)

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