A financial services company is developing a generative AI (GenAI) application that handles customer information. The application must meet strict regulatory and compliance requirements. The company limits the amount of data collected and deletes training data after a defined retention period.Which responsible AI dimension does this practice represent?
Answer(s): A
Limiting data collection and deleting training data after a defined retention period are privacy and security practices. They reduce unnecessary exposure of customer information and support regulatory requirements for data minimization, retention, and protection.
A company is using Amazon SageMaker AI to develop AI/ML solutions. The company must use only approved data for model training. The AI/ML solutions must comply with company policy and ethical guidelines.Which solution will meet these requirements?
Amazon SageMaker Catalog enforces governance and data access controls by allowing organizations to manage, approve, and control which datasets and assets are available for model training, ensuring that only approved data is used and that development complies with company policies and ethical guidelines.
A company wants to use foundation models (FMs) for multiple use cases, including content summarization,code generation, and customer service AI assistants.Which solution will implement FMs MOST cost-effectively?
Selecting the smallest foundation model that meets the performance requirements helps control inference cost while still achieving the needed output quality for each use case. Different tasks have different complexity levels, so matching model size to the task is the most cost-effective approach.
A social media company wants to use a large language model (LLM) to summarize messages. The company has chosen a few LLMs that are available on Amazon SageMaker JumpStart. The company wants to compare the generated output toxicity of these models.Which strategy gives the company the ability to evaluate the LLMs with the LEAST operational overhead?
Answer(s): B
Automatic model evaluation is the strategy that allows the company to evaluate the LLMs with the least operational overhead. This method leverages automated tools and processes to assess the toxicity or quality of the generated output without the need for manual intervention or crowd-sourced input. By using pre-built evaluation metrics or toxicity detection models, the company can quickly and efficiently evaluate multiple models without the complexity and time required for human evaluations.
A company wants its AI assistant to check live inventory levels from the company's warehouse system.Which option gives the AI assistant the ability to access real-time data from external systems?
Model Context Protocol (MCP) enables AI assistants to connect with external tools, APIs, and data sources,allowing them to retrieve real-time information such as live warehouse inventory levels.
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