A company needs to deploy a large language model for a customer service chatbot. They have a limited budget and need to minimize latency. They are considering using a managed API service versus self-hosting an open-source model. Which factor should they primarily consider when making this decision?

The cost of the managed API versus the infrastructure cost of self-hosting

The number of developers on the team

The size of the model's training dataset

The latency requirements and the operational overhead the company can handle

A company wants to deploy a model for real-time inference. They have a pre-trained model that is too large to run on a single GPU instance within their budget. They are considering using a managed API service that offers a smaller, distilled version of the model. Which trade-off should they primarily consider?

The number of users the model will serve

The accuracy of the distilled model versus the cost of running the larger model

The size of the training dataset

The latency of the managed API versus the latency of self-hosting

AWSCertified AI Practitioner

Domain 1Objective 3

Task Statement 1.3: Describe the AI/ML Development Lifecycle. AIF-C01 Practice Questions (Page 2)

Part of the Content Domain 1: Fundamentals of AI and ML domain, which makes up ~20% of our current practice bank. AWS does not publish an official question count, but from its 90-minute exam (~35–60 total, ~7–12 in this domain), expect 2–4 from this objective — we provide 29 practice questions to prepare you well beyond it. (estimate)

29questions here

6free pages

7concepts

Questions 6–10

6expert · hard
A company needs to deploy a large language model for a customer service chatbot. They have a limited budget and need to minimize latency. They are considering using a managed API service versus self-hosting an open-source model. Which factor should they primarily consider when making this decision?
Select an answer first
7foundation · easy
Which AWS service is primarily used for building, training, and deploying machine learning models at scale?
Select an answer first
8foundation · easy
Which business metric for evaluating an ML model focuses on the cost incurred to serve each individual user of the model?
Select an answer first
9expert · hard
A company wants to deploy a model for real-time inference. They have a pre-trained model that is too large to run on a single GPU instance within their budget. They are considering using a managed API service that offers a smaller, distilled version of the model. Which trade-off should they primarily consider?
Select an answer first
10foundation · easy
Which business metric for evaluating an ML model measures the net financial benefit generated by the model relative to its total cost?
Select an answer first

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Task Statement 1.3: Describe the AI/ML Development Lifecycle. AIF-C01 Practice Questions (Page 2)

Questions 6–10

A company needs to deploy a large language model for a customer service chatbot. They have a limited budget and need to minimize latency. They are considering using a managed API service versus self-hosting an open-source model. Which factor should they primarily consider when making this decision?

Which AWS service is primarily used for building, training, and deploying machine learning models at scale?

Which business metric for evaluating an ML model focuses on the cost incurred to serve each individual user of the model?

Which business metric for evaluating an ML model measures the net financial benefit generated by the model relative to its total cost?

Keep studying — Content Domain 1: Fundamentals of AI and ML