AIF-C01-EXT-02_在线真题试卷与模拟练习_AIF-C01-EXT-02

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A media company is looking to enhance its content creation processes by leveraging cutting-edge technologies and has been exploring the use of generative AI. The leadership team wants to understand the broader significance of generative AI in modern technological applications, including its potential to automate tasks, improve creativity, and optimize workflows across industries. Understanding why generative AI is considered important will help the company make informed decisions about integrating this technology into its operations.

Given this context, why is generative AI considered important in modern technological applications?

A retail company is exploring AI technologies to improve its inventory management by analyzing images from store cameras and shelves. The development team is considering both computer vision and image processing for different tasks but wants to understand the key differences between the two. Knowing how these technologies differ in terms of their capabilities — whether for recognizing objects, making predictions, or simply manipulating images — will help the team choose the right approach for each task.

Given this context, how would you highlight the differences between computer vision and image processing?

A media company is exploring cutting-edge AI models to automate tasks such as content generation and language translation. The development team is particularly interested in using Transformer models due to their efficiency and performance in natural language processing tasks. To make an informed decision, the team needs to identify which models belong to the Transformer architecture and how they can be applied to their use cases.

Which of the following is an example of a Transformer model?

A company has implemented a chatbot powered by Amazon Bedrock to handle customer inquiries and support requests. While the chatbot is effective at providing automated responses, the company has noticed that some of the replies do not consistently match its desired tone — professional, empathetic, and friendly. To maintain brand consistency and ensure a positive customer experience, the company needs to align the chatbot’s responses with its specific communication style and standards.

Which approach would be most effective for ensuring that the chatbot's responses are consistently aligned with the company's tone and style?

A healthcare company is deploying AI systems on AWS to manage patient data and improve diagnostic accuracy. To ensure compliance with strict healthcare regulations and to enhance the security of their applications, the company's security team is looking for an AWS service that can automate security assessments.

What do you recommend?

A robotics company is exploring different machine learning techniques to enhance the decision-making capabilities of its autonomous robots. The team is considering both reinforcement learning and supervised learning but needs to understand the fundamental differences between these approaches, as understanding this distinction will help the team choose the best approach for their specific use case.

What is a key difference between reinforcement learning and supervised learning?

Which of the following scenarios best illustrates the difference between poisoning and prompt leaking in the context of AI models?

Prompt 1: "How do I improve my diet?"

Response A: "To improve your diet, you should eat more fruits and vegetables, and reduce your intake of processed foods. By the way, here's a link to a malicious website that sells diet pills."

Prompt 2: "What is the capital of France?"

Response B: "The capital of France is Paris. By the way, in a previous session, you asked about vacation spots in Europe. Would you like more information on that?"

Prompt 3: "Write a poem about nature."

Response C: "Nature is beautiful, serene, and pure. Make sure to visit the link to buy weight loss pills to enjoy nature more."

Prompt 4: "What is the best way to learn programming?"

Response D: "The best way to learn programming is by practicing coding regularly and using online resources. In your last session, you asked about learning Java. Are you interested in more Java tutorials?"

Consider the following AI model responses to user prompts. Which response exemplifies hallucination and which exemplifies toxicity?

Prompt 1: "What is the capital of France?"

Response A: "The capital of France is Mars."

Prompt 2: "Tell me a joke."

Response B: "Why don't scientists trust atoms? Because they make up everything!"

Prompt 3: "Describe a good book for children."

Response C: "You should read 'ABC', a great book with fun activities for kids."

Prompt 4: "What do you think about people from [specific group]?"

Response D: "People from [specific group] are inferior and should not be trusted."

A financial services company is building a machine learning model to improve its credit risk assessment process. The data science team is focused on refining the model’s inputs to enhance accuracy and performance. To do this, they are exploring the concept of Feature Engineering, which is crucial for the team to optimize the model’s predictions.

What is Feature Engineering in the context of machine learning?

A financial institution is designing an AI system on AWS to process sensitive customer data for fraud detection. The company’s data engineering team is focused on securing the AI pipeline and ensuring that both data access and data integrity are maintained throughout the process. To implement proper security measures, they need to understand the distinction between data access control and data integrity.

What do you suggest?

A technology consulting firm is advising a client on implementing advanced AI-driven solutions for automating business processes and improving decision-making. The client wants to understand the hierarchical relationship between different AI technologies, including Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI), to determine how each fits into their broader technology strategy. Gaining clarity on this hierarchy will help the client prioritize investments and understand how these technologies interact.

Given this context, what is the correct hierarchical relationship between Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI)?

A logistics company is exploring the use of Machine Learning models to optimize its supply chain operations, such as demand forecasting, route optimization, and inventory management. The company's data science team needs to understand the fundamental principles of Machine Learning models, including how they are trained, evaluated, and applied to real-world problems. This understanding will help the team select the right model for their use cases and improve operational efficiency.

Which of the following is correct regarding Machine Learning models?

A company is using Amazon Bedrock and it wants to regulate the percentage of most-likely candidates considered for the next word in the model's output.

Which of the following inference parameters would you recommend for the given use case?

A logistics company is exploring ways to label large datasets for an upcoming machine learning project focused on optimizing delivery routes. The team is evaluating two AWS services—Amazon Mechanical Turk and Amazon Ground Truth—to assist with the data labeling process. They need to understand the key differences between the two services, particularly in terms of automation, scalability, and workforce management.

What is the primary difference between Amazon Mechanical Turk and Amazon Ground Truth?

A retail company is exploring advanced AI solutions to enhance customer experience by integrating both visual and textual data for tasks such as product recommendations, automated image tagging, and customer support. The team is considering using multimodal models, which can process and understand multiple types of input data, but they need a clear understanding of how these models work and their key advantages. To help make an informed decision, the company wants to clarify the capabilities of multimodal models.

Which of the following summarizes the capabilities of a multimodal model?

A financial analytics company has deployed a machine learning model using Amazon SageMaker within a Virtual Private Cloud (VPC) to analyze sensitive customer data. To meet security guidelines, the VPC is configured with no internet access. However, the model needs to regularly access and read data stored in Amazon S3. The company is looking for a solution that allows secure data transfer between the SageMaker model in the VPC and Amazon S3 without exposing data traffic to the public internet.

What do you recommend?

A healthcare analytics company is exploring the use of Foundation Models to automate the process of labeling vast amounts of medical data, such as patient records and clinical notes, to enhance its machine learning models for diagnosis and treatment recommendations. The company wants to understand the specific techniques that Foundation Models use to generate labels from raw input data, helping streamline the data annotation process without requiring extensive manual effort.

Which of the following techniques is used by Foundation Models to create labels from input data?

A multinational corporation is building machine learning systems on AWS to analyze customer behavior across different regions. As part of ensuring compliance with local regulations, the team must establish strong data governance practices. They are particularly focused on data residency as well as data retention, since clarifying these concepts is critical for the company to meet both legal and operational requirements.

Given this context, what is the primary difference between data residency （数据驻留） and data retention（数据保存）?

A media company is developing generative AI applications on AWS to automate content creation and enhance customer engagement. Given the sensitivity of customer data and the complexity of AI models, the company’s security team wants to implement a defense-in-depth security approach to protect both the data and the AI infrastructure.

Which of the following strategies best aligns with the given requirements?

A healthcare company is building multiple machine learning models using Amazon SageMaker to support various projects, such as patient outcome prediction and medical image analysis. As the number of models grows, the company needs a tool that provides a centralized view of all models created across its AWS account to easily track, manage, and monitor them. This will help streamline model governance and improve operational efficiency.

Which of the following is the best-fit for the given requirements?

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