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NEW QUESTION # 32
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?
Answer: D
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 # 33
A company wants to implement a single environment for both data and AI development. Developers across different teams must be able to access the environment and work together. The developers must be able to build and share models and generative AI applications securely in the environment.
Which AWS solution will meet these requirements?
Answer: D
Explanation:
Amazon SageMaker Unified Studio provides a collaborative, secure, and centralized environment for end- to-end data, machine learning, and generative AI development. AWS documentation describes Unified Studio as a single interface where teams can prepare data, build models, train and deploy machine learning solutions, and develop generative AI applications.
In this use case, multiple teams must collaborate in a shared environment. SageMaker Unified Studio supports role-based access control, shared workspaces, and secure resource management, allowing developers to safely collaborate without compromising data or models. AWS highlights that Unified Studio integrates notebooks, pipelines, model development tools, and generative AI workflows into a consistent experience.
The service also supports model sharing, versioning, and reuse, enabling teams to build upon each other's work. This directly satisfies the requirement to build and share both traditional ML models and generative AI applications securely.
The other options are not suitable. Amazon Lex is a conversational AI service, not a development environment. Amazon Bedrock PartyRock is a no-code generative AI playground and is not intended for enterprise collaboration. Amazon Q Developer focuses on developer productivity and code assistance, not unified AI development environments.
AWS positions SageMaker Unified Studio as the foundation for collaborative AI development at scale, making it the correct choice.
NEW QUESTION # 34
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?
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 References:
* 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 # 35
A company wants to use its documents as a knowledge base for a large language model (LLM) in a Retrieval Augmented Generation (RAG) solution.
Which solution will meet these requirements?
Answer: C
NEW QUESTION # 36
Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?
Answer: B
NEW QUESTION # 37
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