AIF-C01 Dumps Free, Reliable AIF-C01 Test Experience
AIF-C01 Dumps Free, Reliable AIF-C01 Test Experience
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Tags: AIF-C01 Dumps Free, Reliable AIF-C01 Test Experience, AIF-C01 Braindump Free, AIF-C01 Latest Examprep, Valid AIF-C01 Test Preparation
Why do so many people determine to take part in Amazon AIF-C01 exam? Owing a nice certification will not only testify your professional skills and qualification but also show your knowledge and ability, it will be useful for your career. AIF-C01 New Test Bootcamp materials will be valid and useful for your test. If you get a certification, you will be regards as knowledgeable expert. Now there is a large demand for these skillful senior engineers.
Amazon AIF-C01 Exam Syllabus Topics:
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High Pass-Rate Amazon - AIF-C01 - AWS Certified AI Practitioner Dumps Free
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Amazon AWS Certified AI Practitioner Sample Questions (Q25-Q30):
NEW QUESTION # 25
A company needs to choose a model from Amazon Bedrock to use internally. The company must identify a model that generates responses in a style that the company's employees prefer.
What should the company do to meet these requirements?
- A. Use public model leaderboards to identify the model.
- B. Use the model InvocationLatency runtime metrics in Amazon CloudWatch when trying models.
- C. Evaluate the models by using a human workforce and custom prompt datasets.
- D. Evaluate the models by using built-in prompt datasets.
Answer: C
Explanation:
To determine which model generates responses in a style that the company's employees prefer, the best approach is to use a human workforce to evaluate the models with custom prompt datasets. This method allows for subjective evaluation based on the specific stylistic preferences of the company's employees, which cannot be effectively assessed through automated methods or pre-built datasets.
* Option B (Correct): "Evaluate the models by using a human workforce and custom prompt datasets": This is the correct answer as it directly involves human judgment to evaluate the style and quality of the responses, aligning with employee preferences.
* Option A: "Evaluate the models by using built-in prompt datasets" is incorrect because built-in datasets may not capture the company's specific stylistic requirements.
* Option C: "Use public model leaderboards to identify the model" is incorrect as leaderboards typically measure model performance on standard benchmarks, not on stylistic preferences.
* Option D: "Use the model InvocationLatency runtime metrics in Amazon CloudWatch" is incorrect because latency metrics do not provide any information about the style of the model's responses.
AWS AI Practitioner References:
* Model Evaluation Techniques on AWS: AWS suggests using human evaluators to assess qualitative aspects of model outputs, such as style and tone, to ensure alignment with organizational preferences
NEW QUESTION # 26
A medical company deployed a disease detection model on Amazon Bedrock. To comply with privacy policies, the company wants to prevent the model from including personal patient information in its responses. The company also wants to receive notification when policy violations occur.
Which solution meets these requirements?
- A. Use Amazon Macie to scan the model's output for sensitive data and set up alerts for potential violations.
- B. Configure AWS CloudTrail to monitor the model's responses and create alerts for any detected personal information.
- C. Implement Amazon SageMaker Model Monitor to detect data drift and receive alerts when model quality degrades.
- D. Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms for notification of policy violations.
Answer: D
Explanation:
Guardrails for Amazon Bedrock provide mechanisms to filter and control the content generated by models to comply with privacy and policy requirements. Using guardrails ensures that sensitive or personal information is not included in the model's responses. Additionally, integrating Amazon CloudWatch alarms allows for real- time notification when a policy violation occurs.
* Option C (Correct): "Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms for notification of policy violations": This is the correct answer because it directly addresses both the prevention of policy violations and the requirement to receive notifications when such violations occur.
* Option A: "Use Amazon Macie to scan the model's output for sensitive data" is incorrect because Amazon Macie is designed to monitor data in S3, not to filter real-time model outputs.
* Option B: "Configure AWS CloudTrail to monitor the model's responses" is incorrect because CloudTrail tracks API activity and is not suited for content moderation.
* Option D: "Implement Amazon SageMaker Model Monitor to detect data drift" is incorrect because data drift detection does not address content moderation or privacy compliance.
AWS AI Practitioner References:
* Guardrails in Amazon Bedrock: AWS provides guardrails to ensure AI models comply with content policies, and using CloudWatch for alerting integrates monitoring capabilities.
NEW QUESTION # 27
A company has petabytes of unlabeled customer data to use for an advertisement campaign. The company wants to classify its customers into tiers to advertise and promote the company's products.
Which methodology should the company use to meet these requirements?
- A. Unsupervised learning
- B. Reinforcement learning
- C. Supervised learning
- D. Reinforcement learning from human feedback (RLHF)
Answer: A
NEW QUESTION # 28
Which term describes the numerical representations of real-world objects and concepts that AI and natural language processing (NLP) models use to improve understanding of textual information?
- A. Binaries
- B. Tokens
- C. Embeddings
- D. Models
Answer: C
NEW QUESTION # 29
A company needs to build its own large language model (LLM) based on only the company's private data.
The company is concerned about the environmental effect of the training process.
Which Amazon EC2 instance type has the LEAST environmental effect when training LLMs?
- A. Amazon EC2 P series
- B. Amazon EC2 G series
- C. Amazon EC2 Trn series
- D. Amazon EC2 C series
Answer: C
Explanation:
The Amazon EC2 Trn series (Trainium) instances are designed for high-performance, cost-effective machine learning training while being energy-efficient. AWS Trainium-powered instances are optimized for deep learning models and have been developed to minimize environmental impact by maximizing energy efficiency.
* Option D (Correct): "Amazon EC2 Trn series": This is the correct answer because the Trn series is purpose-built for training deep learning models with lower energy consumption, which aligns with the company's concern about environmental effects.
* Option A: "Amazon EC2 C series" is incorrect because it is intended for compute-intensive tasks but not specifically optimized for ML training with environmental considerations.
* Option B: "Amazon EC2 G series" (Graphics Processing Unit instances) is optimized for graphics- intensive applications but does not focus on minimizing environmental impact for training.
* Option C: "Amazon EC2 P series" is designed for ML training but does not offer the same level of energy efficiency as the Trn series.
AWS AI Practitioner References:
* AWS Trainium Overview: AWS promotes Trainium instances as their most energy-efficient and cost- effective solution for ML model training.
NEW QUESTION # 30
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