AWS Certified AI Practitioner AIF-C01 Practice Question
An insurance startup wants to deploy a text-generation foundation model to power a customer-support chatbot that must respond in English, Spanish, and Japanese without any language-specific fine-tuning. Which model-selection criterion should the team prioritize when evaluating pre-trained models?
Because the chatbot must operate in several languages out of the box, the team should choose a foundation model that already provides strong multi-lingual support. Other factors-such as latency, model size, or additional modalities-do not directly guarantee that the model can generate high-quality responses in multiple languages without extra training.
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What is a foundation model?
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Why is multi-lingual support important for a chatbot?
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How can fine-tuning impact multi-lingual models?
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What does multi-lingual support mean in a pre-trained model?
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Why is built-in multi-lingual support better than fine-tuning for language-specific scenarios?
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How can you evaluate if a foundation model has strong multi-lingual support?
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AWS Certified AI Practitioner AIF-C01
Applications of Foundation Models
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