AWS Certified AI Practitioner AIF-C01 Practice Question
A development team will build a multilingual chatbot and requires model responses in less than 50 milliseconds. When choosing a pre-trained foundation model, which selection criteria are the MOST important for this use case?
Availability of parameter-efficient fine-tuning and RAG features
The key needs are very low response time and the ability to understand and generate several languages. Latency determines whether each model inference can finish within the 50 ms budget, while multilingual support ensures the chatbot can serve users in multiple languages. Cost, model size, complexity, or fine-tuning methods are secondary for the stated requirements because they do not directly guarantee fast replies or language coverage.
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How do AI models provide multilingual support?
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Why is cost less important than latency and multilingual support in this use case?
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AWS Certified AI Practitioner AIF-C01
Applications of Foundation Models
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