サンプル問題 1： Leadership needs to populate a dynamic form field with a summary or description created by a large language model (LLM) to facilitate more productive conversations with customers. Leadership also wants to keep a human in the loop to be considered in their AI strategy. Which prompt template type should the AI Specialist recommend?
A: Sales Email
B: Field Generation
C: Record Summary
正解：B
Explanation: The correct answer is Field Generation because this template type is designed to dynamically populate form fields with content generated by a large language model (LLM). In this scenario, leadership wants a dynamic form field that contains a summary or description generated by AI to aid customer interactions. Additionally, they want to keep a human in the loop, meaning the generated content will likely be reviewed or edited by a person before it's finalized, which aligns with the Field Generation prompt template. Field Generation: This prompt type allows you to generate content for specific fields in Salesforce, leveraging large language models to create dynamic and contextual information. It ensures that AI content is available within the record where needed, but it allows human oversight or review, supporting the "human-in-the-loop" strategy. Sales Email: This prompt type is mainly used for generating email content for outreach or responses, which doesn't align directly with populating fields in a form. Record Summary: While this option might seem close, it is typically used to summarize entire records for high-level insights rather than filling specific fields with dynamic content based on AI generation. Salesforce AI Specialist Reference: You can explore more about these prompt templates and AI capabilities through Salesforce documentation and official resources on Prompt Builder: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_templates_overview.htm
サンプル問題 2： Universal Containers is considering leveraging the Einstein Trust Layer in conjunction with Einstein Generative AI Audit Data. Which audit data is available using the Einstein Trust Layer?
A: Response accuracy and offensiveness score
B: Hallucination score and bias score
C: Masked data and toxicity score
正解：C
Explanation: Universal Containers is considering the use of the Einstein Trust Layer along with Einstein Generative AI Audit Data. The Einstein Trust Layer provides a secure and compliant way to use AI by offering features like data masking and toxicity assessment. The audit data available through the Einstein Trust Layer includes information about masked data― which ensures sensitive information is not exposed―and the toxicity score, which evaluates the generated content for inappropriate or harmful language. Reference: Salesforce AI Specialist Documentation - Einstein Trust Layer: Details the auditing capabilities, including logging of masked data and evaluation of generated responses for toxicity to maintain compliance and trust.
サンプル問題 3： Universal Containers wants to make a sales proposal and directly use data from multiple unrelated objects (standard and custom) in a prompt template. What should the AI Specialist recommend?
A: Create a Flex template to add resources with standard and custom objects as inputs.
B: Create a prompt template passing in a special custom object that connects the records temporarily,
C: Create a prompt template-triggered flow to access the data from standard and custom objects.
正解：A
Explanation: Universal Containers needs to generate a sales proposal using data from multiple unrelated standard and custom objects within a prompt template. The most effective way to achieve this is by using a Flex template. Flex templates in Salesforce allow AI specialists to create prompt templates that can accept inputs from multiple sources, including various standard and custom objects. This flexibility enables the direct use of data from unrelated objects without the need to create intermediary custom objects or complex flows. Reference: Salesforce AI Specialist Documentation - Flex Templates: Explains how Flex templates can be utilized to incorporate data from multiple sources, providing a flexible solution for complex data requirements in prompt templates.
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