AIF-C01 ANSWERS REAL QUESTIONS | RELIABLE AIF-C01 BRAINDUMPS FILES

AIF-C01 Answers Real Questions | Reliable AIF-C01 Braindumps Files

AIF-C01 Answers Real Questions | Reliable AIF-C01 Braindumps Files

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Tags: AIF-C01 Answers Real Questions, Reliable AIF-C01 Braindumps Files, AIF-C01 Simulation Questions, New AIF-C01 Test Online, New AIF-C01 Test Fee

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Amazon AWS Certified AI Practitioner Sample Questions (Q150-Q155):

NEW QUESTION # 150
A company wants to create an application by using Amazon Bedrock. The company has a limited budget and prefers flexibility without long-term commitment.
Which Amazon Bedrock pricing model meets these requirements?

  • A. On-Demand
  • B. Model customization
  • C. Provisioned Throughput
  • D. Spot Instance

Answer: A

Explanation:
Amazon Bedrock offers an on-demand pricing model that provides flexibility without long-term commitments. This model allows companies to pay only for the resources they use, which is ideal for a limited budget and offers flexibility.
* Option A (Correct): "On-Demand": This is the correct answer because on-demand pricing allows the company to use Amazon Bedrock without any long-term commitments and to manage costs according to their budget.
* Option B: "Model customization" is a feature, not a pricing model.
* Option C: "Provisioned Throughput" involves reserving capacity ahead of time, which might not offer the desired flexibility and could lead to higher costs if the capacity is not fully used.
* Option D: "Spot Instance" is a pricing model for EC2 instances and does not apply to Amazon Bedrock.
AWS AI Practitioner References:
* AWS Pricing Models for Flexibility: On-demand pricing is a key AWS model for services that require flexibility and no long-term commitment, ensuring cost-effectiveness for projects with variable usage patterns.


NEW QUESTION # 151
A digital devices company wants to predict customer demand for memory hardware. The company does not have coding experience or knowledge of ML algorithms and needs to develop a data-driven predictive model. The company needs to perform analysis on internal data and external data.
Which solution will meet these requirements?

  • A. Import the data into Amazon SageMaker Canvas. Build ML models and demand forecast predictions by selecting the values in the data from SageMaker Canvas.
  • B. Import the data into Amazon SageMaker Data Wrangler. Create ML models and demand forecast predictions by using SageMaker built-in algorithms.
  • C. Store the data in Amazon S3. Create ML models and demand forecast predictions by using Amazon SageMaker built-in algorithms that use the data from Amazon S3.
  • D. Import the data into Amazon SageMaker Data Wrangler. Build ML models and demand forecast predictions by using an Amazon Personalize Trending-Now recipe.

Answer: A

Explanation:
I'll continue to format the rest. Let me know if you would like me to provide them all in one go or in parts.


NEW QUESTION # 152
A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.
Which business objective should the company use to evaluate the effect of the LLM chatbot?

  • A. Website engagement rate
  • B. Average call duration
  • C. Regulatory compliance
  • D. Corporate social responsibility

Answer: B


NEW QUESTION # 153
A company is using the Generative AI Security Scoping Matrix to assess security responsibilities for its solutions. The company has identified four different solution scopes based on the matrix.
Which solution scope gives the company the MOST ownership of security responsibilities?

  • A. Building an application by using an existing third-party generative AI foundation model (FM).
  • B. Using a third-party enterprise application that has embedded generative AI features.
  • C. Refining an existing third-party generative AI foundation model (FM) by fine-tuning the model by using data specific to the business.
  • D. Building and training a generative AI model from scratch by using specific data that a customer owns.

Answer: D

Explanation:
Building and training a generative AI model from scratch provides the company with the most ownership and control over security responsibilities. In this scenario, the company is responsible for all aspects of the security of the data, the model, and the infrastructure.
Option D (Correct): "Building and training a generative AI model from scratch by using specific data that a customer owns": This is the correct answer because it involves complete ownership of the model, data, and infrastructure, giving the company the highest level of responsibility for security.
Option A: "Using a third-party enterprise application that has embedded generative AI features" is incorrect as the company has minimal control over the security of the AI features embedded within a third-party application.
Option B: "Building an application using an existing third-party generative AI foundation model (FM)" is incorrect because security responsibilities are shared with the third-party model provider.
Option C: "Refining an existing third-party generative AI FM by fine-tuning the model with business-specific data" is incorrect as the foundation model and part of the security responsibilities are still managed by the third party.
AWS AI Practitioner Reference:
Generative AI Security Scoping Matrix on AWS: AWS provides a security responsibility matrix that outlines varying levels of control and responsibility depending on the approach to developing and using AI models.


NEW QUESTION # 154
A company wants to build an ML model by using Amazon SageMaker. The company needs to share and manage variables for model development across multiple teams.
Which SageMaker feature meets these requirements?

  • A. Amazon SageMaker Data Wrangler
  • B. Amazon SageMaker Model Cards
  • C. Amazon SageMaker Feature Store
  • D. Amazon SageMaker Clarify

Answer: C


NEW QUESTION # 155
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